Thongchai Thailand

ACID RAIN: LAKE ACIDITY IN THE ADIRONDACKS

Posted on: March 12, 2019

FIGURE 1: The affected areas of environmental damage attributed to acid rainARP01

 

FIGURE 2: THE CLAIMED DEVASTATION OF THE ADIRONDACKS BY ACID RAINARP02

 

FIGURE 3: LOCATION OF LAKE ACIDITY MEASUREMENTS & EPA REGIONS

FIGURE 4: SO2 EMISSIONS FOR EACH AFFECTED EPA REGIONARP04ARP05ARP06

 

FIGURE 5: RAIN AND LAKE ACIDITY DATAARP08ARP09ARP10ARP11

 

FIGURE 6: HYPOTHESIS TESTS FOR CORRELATION ARP12ARP13

 

FIGURE 7: CORRELATION BETWEEN EMISSIONS AND ACIDITYARP14ARP15ARP16ARP17ARP18ARP19

 

 

FIGURE 8: CORRELATION ANALYSIS RESULTS: SUMMARY TABLEARP20ARP21

 

 

 

[LIST OF POSTS ON THIS SITE]

 

 

 

  1. ABSTRACT: Detrended correlation analysis in the sample period 1992-2015 shows that on an annual time scale the acidity of rain in NY is responsive to the combined anthropogenic SO2 emissions in EPA Regions 1, 2, and 3; but that the acidity of lakes in the Adirondacks is not responsive to the acidity of rain in NY. An attempt to explain lake acidity in terms of dry deposition of anthropogenic SO2 emissions also failed. Our results are consistent with previous research which found no relationship between rain acidity and lake acidity and explained lake acidity in terms of soil chemistry in the catchment area of the lakes.
  2. Anthropogenic emissions of sulfur dioxide (SO2) from industrial combustion of fossil fuels particularly coal became an environmental issue in the 1960s and 1970s because SO2 combines with water in the atmosphere and falls back to the surface in acidic form. Such acid deposition is referred to as acid rain and deemed undesirable because it is thought to kill fish in lakes and streams by increasing the acidity of the water and also to kill trees and damage crops by virtue of its acidity (Schindler, 1988) (Schofield, 1976) (Beamish, 1972) (Siccama, 1982) (Vogelmann, 1988) (Vogelmann, 1985) (Irving, 1981) (Cape, 1993) (Newbery, 1990). In 1970 the Clean Air Act (CAA) Amendment of 1970 was passed and the Environmental Protection Agency (EPA) was formed to enforce it. In 1971 the EPA put in place regulations to limit SO2 emissions from power plants on a per megawatt basis to achieve national air quality standards for SO2 mandated by the 1970 Amendment (Melnick, 2010) (Taylor, 2005). These were command and control regulations that prescribed to each affected firm, the emission reduction targets to be met and the methods to be used to meet them (Cole, 1999). SO2 emissions fell 30% from 1972 to 1982 but with no measurable change in the acidification of lakes and streams, or of the other cited environmental harm associated with SO2 emissions (NAPAP, 1987).
    The two primary methods of lowering SO2 emissions from power plants are fuel switching, which increases variable cost with minimal capital investment requirements, and the installation of scrubbers and sulfur plants, which requires significant capital investment with a minimal effect on operating costs. In general, the optimal combination of these methods would vary among utility firms according to size, location, availability of fuel and technological options, future plans, and management or investor priorities. Also, the cost of cutting emissions in general is likely to vary among power plants according to plant size, level of technological sophistication, and access to technology. Therefore, the cost of meeting command and control regulations varies from firm to firm.
  3. It was in this context that John Dales first proposed that to discover and minimize the marginal cost of aggregate pollution abatement the affected firms should cooperate and work together as a group to cut aggregate emissions of the portfolio of firms and that therefore environmental regulation should address aggregate emissions instead of firm by firm emissions on a command and control basis (Dales, 1968). This idea was first tried by the EPA with the 1977 Amendment to the CAA (EPA, 2001) (Halbert, 1977) and refined into a cap-and-trade emissions trading system called the Acid Rain Program described in Title IV of the 1990 Amendments to the CAA (Popp, 2003) (Waxman, 1991) (Ellerman, 2000). This innovation is recognized as a milestone in environmental regulation. In the cap-and-trade market of the Acid Rain Program2, the EPA issues allowances, or permits to pollute, in units of one million tons of SO2 per year. The sum of the allowances issued for each emission reduction period (ERP)3 is set to the limit or cap on aggregate emissions from all power generation units in the plan. The aggregate cap is gradually reduced in each subsequent ERP in accordance with a fixed emission reduction schedule for the duration of the plan. The allowances are distributed to the individual units in accordance with unit size measured as the total annual heat production in a defined historical reference period for which both heat production and emissions were measured and are known with some degree of certainty. Emissions at each unit are accurately measured during the ERP. At the end of the ERP each unit pays for its emissions with the allowances it had received at the beginning of the year. Units that do not have enough allowances to pay for their emissions are penalized. This mechanism is the cap component of cap-and-trade. The trade component of cap-and-trade is that during the ERP the participating units may trade allowances among themselves or with third parties in a market where clearing prices are determined by bids and asks as in commodities markets with the exception that with a limited number of traders, it is a thin and illiquid market lacking in the power of price discovery enjoyed by deep and liquid commodities markets. Holders of excess allowances, that is, those units that were able to cut emissions more deeply than required, can put their excess allowances up for sale in the emissions trading market at their ask price. Likewise, units that are unable to meet the cap can place buy orders in the emissions market at their bid price. When bids and asks cross the market clears, trades occur, and the marginal price of aggregate emission reduction is discovered (Chan, 2012) (Conniff, 2009) (Dales, 1968) (Ellerman A. , 2002). In this way, emission allowances are traded among the regulated entities and the aggregate emission target is met without forcing each and every unit to cut emissions at the same rate or with the same technology as in command and control regulation. Thereby the overall cost of compliance is lowered to the aggregate marginal cost in accordance with the mechanism described by John Dales (Dales, 1968). There are certain positive features of the market for SO2 emissions that are relevant in its comparison with emerging markets for trading CO2 emissions (Jenkins, 2009). The most important of these is that the regulatory regime of the Acid Rain Program is well defined in terms of geography and legal infrastructure. The regulatory authority of the US Government and the rights and obligations of the regulated utilities are well defined by the constitution and the laws of the United States of America, the powers of the Federal Government, and the provisions of the Clean Air Act and its Amendments in 1970, 1977, and 1990, and Congressional authority that requires the EPA to limit SO2 emissions across state lines. At the same time the rights of the regulated utilities are protected by law and by a well-functioning judiciary.
  4. The purpose of the Acid Rain Program is not to reduce SO2 emissions as an end in itself but as a means to solve the acid rain problem. The acid rain problem is that acid deposition ascribed to anthropogenic SO2 emissions (1) kills trees, (2) increases the acidity of lakes and streams and kills or harms fish, and (3) damages crops. The objective of the Acid Rain Program is to effect a reduction in the environmental harm attributed to anthropogenic SO2 emissions. Therefore, the appropriate measure of the effectiveness or the success of the Acid Rain Program is not just whether SO2 emissions have been reduced but whether the Program has reduced the acidity of rain and the crop damage and the killing of trees and fish attributed to acid rain. The Acid Rain Program was motivated primarily by measurements that showed increased acidity of rainfall in the Northeastern Seaboard of the United States (Figure 1) with devastating environmental effects on high elevation forests in the Northeast particularly on Camel’s Hump Mountain in Vermont and on fish in highland lakes and ponds particularly on the Adirondack Mountains in New York (Figure 2) (Schindler, 1988) (Siccama, 1982). As an evaluation of the effectiveness of the Program we therefore consider whether the environmental concerns with respect the Adirondack Region of New York State (hereafter referred to as the “Adirondacks”) have been adequately addressed by the Acid Rain Program. Specifically, we look at the effect of the Acid Rain Program on the acidity of rain in the state of New York and the acidity of lakes in the Adirondacks. The evaluation of the Acid Rain Program is presented in three parts. Part 1 considers whether the Program achieved its objectives as of this writing. Part 2 looks at the design and efficiency of the emissions trading system for SO2 emissions. Part 3 compares the SO2 emissions trading system with market structures proposed for trading CO2 emissions. This document is Part 1 of this series.
  5. DATA AND METHODS: Historical annual anthropogenic emissions of SO2 are provided by the Socio Economic Data and Application Center of Columbia University country by country on an annual basis from 1850 to 2005 (SEDAC, 2009). The patterns in these data are used to interpolate SO2 emissions for years missing in the EPA data. The primary source of anthropogenic SO2 emissions data in this study is the EPA Air Markets Program Data service (AMPD) which provides annual emissions data state by state for the years 1980, 1985, 1990, and annually from 1995 to 2015 (EPA-AMPD, 2016). The SEDAC data provide “total” SO2 emissions as well as “emissions from coal”. The EPA emission figures for the lower 48 states add up to values that closely match the “emissions from coal” figures in the SEDAC dataset for the years that the two datasets have in common. The year to year patterns in the SEDAC coal data are therefore used to interpolate the EPA emissions data for the missing years between 1990 and 1995. The interpolation yields estimated emission figures for 1992, 1993, and 1994 for the EPA dataset and generates a continuous annual emission data series state by state for the sample period 1992 to 2015. The state by state data are aggregated into data for EPA Regions (Figure 5) (EPA, 2016).
    The study period is chosen as 1992-2015. It is constrained by the availability of acidity data for lakes in the Adirondacks. The lake acidity data are provided by the Adirondack Lakes Survey Corporation (ALSC) as part of their Adirondack Long Term Monitoring (ALTM) program (ALSC, 2016). The dataset used in this study are the average SO4 concentrations in water samples taken from near the surface of lakes and ponds at over forty measuring stations located throughout the Adirondack (Figure 3). A continuous time series of annual mean SO4 concentration data in mg/liter are available from 1992 to 2015. These data constitute out “lake acidity” dataset. The importance of the ALTM lake acidity dataset in the evaluation of the Acid Rain Program is underscored by the rationale cited by the ALSC for their ALTM program. The text of this statement taken from the ALSC website is included in Figure 3 in abbreviated form along with the map showing the location of the ALTM measuring stations. The sensitivity of Adirondack lake acidity to acid rain and thereby to anthropogenic SO2 emissions is widely recognized (ALSC, 2016) (Driscoll, 2003) and this sensitivity forms the basis of our empirical test of the hypotheses that relate lake acidity to rain acidity and rain acidity to SO2 emissions. Acid deposition data are provided by the National Atmospheric Deposition Program (NADP, 2016) which maintains a large number of stations for the measurement of pollutants in precipitation (rain, snow, sleet, and hail). Included in the data are measurements of SO4 concentration in mg/liter weighted by the amount of precipitation. Since the focus of this work is the acidity of lakes in the Adirondack Region which is located wholly within New York State (NY), the relevant NADP data are identified as those taken from 21 NADP stations located within NY. The NADP dataset provides 4,127 SO4 acid deposition measurements taken at the 21 NADP measuring stations in NY during the period 1979 to 2015. These values are aggregated into annual means from 1992 to 2015, and this time series serves as the “rain acidity” measure in our study.
    We test the hypotheses that (1) rain acidity is responsive to anthropogenic SO2 emissions at an annual time scale, (2) lake acidity is responsive to rain acidity at an annual time scale, and (3) lake acidity is responsive directly to anthropogenic SO2 emissions at an annual time scale. For hypothesis #2, the relevant data are well defined as mean rain acidity in NY and mean lake acidity in the Adirondacks but for hypotheses #1 and #3, it is necessary to identify the relevant geographical area for SO2 emissions. Four different geographical extents that include NY are considered. They are EPA Regions 1, and 2, EPA Regions 1, 2, and 3, EPA Regions 1, 2, 3, and 4, and EPA Regions 1, 2, 3, and 5. Hypotheses #1 and #3 are tested four times once for each geographical extent. Thus there are 9 hypothesis tests, four for emissions and rain acidity, four for emissions and lake acidity, and one for rain acidity and lake acidity.
    The possibility of a direct relationship between anthropogenic SO2 emissions and lake acidity that does not act through acid rain derives from the “dry deposition” theory (Cosby, 1985) (Delmelle, 2001) (Driscoll, 2003) (Driscoll, 2001) (Graedel, 1989). It holds that SO4 in dry sulfate form in the atmosphere can affect lake acidity independent of precipitation of any form. The hypotheses are tested using detrended correlation analysis. Detrending is necessary to determine if a positive relationship exists that could be interpreted in terms of a theory of causation in a year to year annual time scale net of a shared drift in time in terms of overall trend during the sample period (Chatfield, 1989) (Prodobnik, 2008) (Munshi, 2016). Pearson’s correlation coefficient is computed with Excel’s CORREL () function and Bowley’s procedure is used to estimate the standard deviation of the correlation coefficient. One tailed t-tests are used to test the null hypothesis H0: ρ>0 against HA: ρ≤0. The test corresponds with the assumed positive relationships among the variables studied. For example, SO2 emissions are thought to increase not decrease rain acidity and rain acidity is thought to increase and not decrease lake acidity. All hypothesis tests are made at a maximum false positive error rate of α=0.001 per comparison consistent with “Revised standards for statistical evidence” published by the NAS to address an unacceptable rate of irreproducible results in published research (Johnson V. , 2013) (Siegfried, 2010). Since 9 comparisons are made each at α(comparison)= 0.001, the study-wide maximum false positive error rate is estimated as α(study) = 0.009 (Holm, 1979). This means that there is a 0.9% probability of at least one false positive result in nine tries with samples taken from the H0 distributions. All data and computational detains used in this work are available in an online data archive (Munshi, SO2-Part1-Archive, 2016).
  6. DATA ANALYSIS AND RESULTS: Data for anthropogenic SO2 emissions in each of eight EPA regions (Figure 5) from 1980 to 2015 are displayed in Figure 4. It shows a wide range of SO2 emissions at the inception of the Acid Rain Program in 1995 from over 4,000 kilo tons per year (KTY) to less than 400 KTY. With the exception of regions 6&8, where emissions are relatively low to begin with, all regions show a steep decline in SO2 emissions from 1995 to 2015.
    The bottom panel of Figure 4 compares the rate of decline in SO2 emissions from coal in the USA (SEDAC, 2009) before the Acid Rain Program (1970-1994) with the rate of decline in the Acid Rain Program era since 1995. The comparison indicates a four-fold increase in the rate of decline in SO2 emissions since 1995. Figure 5 displays the data for the acidity of precipitation in the state of New York (left panel) and the acidity of lakes and streams in the Adirondacks (right panel) for the sample period 1992-2015. The sample period is constrained by the availability of lake data. The graphic display of the data indicates a dramatic decline in SO4 acidity5 of rain in NY and of lakes in the Adirondacks over a period when anthropogenic SO2 emissions have also declined (Figure 4). To determine whether these declining trends are related at an annual time scale we carry out detrended correlation analysis among anthropogenic SO2 emissions, SO4 acidity of rain in NY, and SO4 acidity of lakes in the Adirondacks. Natural emissions of SO2, though much larger than anthropogenic emissions (HSDB, 2016), are not included in this analysis because they are sporadic and random with great uncertainty and therefore unquantifiable on an annual basis. The analysis for the relationship at an annual time scale between acidity of rain in NY and the acidity of lakes in the Adirondacks is presented graphically in Figure 5. A high correlation of R = 0.9612 is observed between the time series in the lower left panel of Figure 5. This correlation can be described as being derived from two sources. They are (1) the common and perhaps incidental direction of the drift in time of the two time series being compared and (2) the responsiveness of the acidity of lakes to the acidity or rain at an annual time scale. It is the second effect that is relevant to a theory of causation6 that relates lake acidity to the acidity of rain and it is extracted from the overall correlation with detrended correlation analysis (Chatfield, 1989) (Prodobnik, 2008) (Munshi, 2016). The detrended correlation at an annual time scale is depicted graphically in the bottom right panel of Figure 5 and it shows some evidence of a positive correlation. The highlighted column in Figure 6 shows that the value of the detrended correlation coefficient is computed as R = 0.3655 and using Bowley’s procedure we estimate its standard deviation as S = 0.1984 (Bowley, 1928). The null hypothesis H0: ρ≤0 against HA: ρ>0 is tested with the t-distribution and the one-tail pvalue is computed as p=0.03951. At a maximum false positive error rate of α=0.001 per comparison (Johnson V. , 2013), we find that the pvalue > α and we therefore fail to reject H0 in this case and conclude that the data do not provide sufficient evidence that lake acidity is responsive to rain acidity at an annual time scale. This result is consistent with prior research that found no correlation between the acidity of rain and the acidity of lakes and streams and attributed changes in the acidity of lakes not to the acidity of rain but to the acidity of the soil in the catchment area or drainage basin through which rainwater drains into lakes and streams (NAPAP, 1987) (Krug, 1989) (Cosby, 1985). Soil chemistry of the catchment area was found to be the dominant factor that determines the acidity of lakes and streams in which direct rainfall is an insignificant source of water.
    We now test the responsiveness of rain acidity in NY to anthropogenic SO2 emissions from a relevant geographical area. Four different geographical areas are tested for relevance in terms of SO2 emissions that can be related to the SO4 acidity of rain in NY. Statistically significant results are found in two of these emission regions (Figure 6). The results for the geographical area defined as EPA Regions 1, 2, and 3 are shown in the highlighted column of Figure 6 and depicted graphically in Figure 7. The bottom right panel of Figure 10 appears to show evidence that the acidity of rain in NY is responsive to SO2 emissions In EPA Regions 1, 2, and 3 at an annual time scale and this visual intuition is confirmed in the highlighted column of Figure 6. These results provide strong evidence that the SO4 acidity of precipitation in NY is related to anthropogenic SO2 emissions in the relevant geographical extent. The results appear to be paradoxical. If anthropogenic SO2 emissions explain the acidity of rain in New York but the acidity of rain in NY does not explain the acidity of lakes in the Adirondacks, then what explains the observed changes in the acidity of lakes in the Adirondacks? One possibility is the role played by “dry deposition” of sulfates. The dry deposition hypothesis implies that anthropogenic SO2 emissions can impose a direct effect on the acidification of lakes independent of acid rain. We test this hypothesis with detrended correlation analysis between SO4 acidity of lakes in the Adirondacks and SO2 emissions in the four EPA Regions described in Figure 6. The test for EPA regions 1, 2, and 3 is depicted graphically in Figure 11 and summarized in the highlighted column of Figure 12. Since the pvalue of p=0.00353 is greater than our comparison α=0.001, we fail to reject H0 and conclude that the data do not provide sufficient evidence that changes in the SO4 acidity of lakes in the Adirondacks can be explained in terms of the sum of SO2 emissions from EPA regions 1, 2, and 3 at an annual time scale. Three other emission regions are tested (Figure 12). No statistically significant result is found.
  7. SUMMARY AND CONCLUSIONS: The Acid Rain Program described in Title IV of the 1990 Amendments to the Clean Air Act of the USA was a response to two high profile environmental events of the 1970s and 1980s in the Northeast region of the USA (Figure 1). First, a high elevation boreal forest of red spruce on Camel’s Hump Mountain in Vermont was found to contain a large number of dead or dying trees (Siccama, 1982) (Johnson A. , 1983) (Vogelmann, 1988) (NAPAP, 1987) (Vogelmann, 1985) (Cape, 1993) and secondly, lakes and ponds in the Adirondacks in New York8 showed an increase in acidity and simultaneously a decrease in the populations of fish and other aquatic creatures9 (Cowling, 1982) (Cowling, 1990) (Russell, 1993) (Garland, 1988) (NAPAP, 1987) (Beamish, 1972) (Krug, 1989) (Wildavsky, 1997). These discoveries came on the heels of the discovery of “acid rain”, a reference to a high level of acidity of precipitation (rain, sleet, hail, and snow) (NADP, 2016).
    Taking note of more than 4,000 KTY of SO2 emissions from coal burning power plants mostly in the states to the west and south of the affected areas (EPA, 2016), environmental science developed a theoretical framework that connected these events in a causation chain. According to this theory anthropogenic SO2 emissions cause acid rain. Acid rain kills red spruce in Camel’s Hump Mountain and acidifies lakes in the Adirondacks. Acid lakes in turn kill aquatic life in the lakes and ponds of the Adirondacks. The Acid Rain Program is based on this theoretical assessment (EPA, 2016). Our evaluation is based on the principle that environmental programs must be judged based on achievement of the environmental objectives at the end of the chain of causation and not on intermediate results (Keith, 1983) (Coen, 2000). It is assumed that these effects occur within one year and that they can therefore be measured at an annual time scale (Langner, 1991) (Cosby B. , 1985) (Larssen, 2000) (NAPAP, 1987) (NAPAP, 2003) (NAPAP, 2011). Although a broader interpretation could be made, we identify the environmental goals of the Acid Rain Program as two-fold: first, to restore the health of the high elevation boreal forest particularly red spruce on Camel’s Hump Mountain that is alleged to have been damaged by the acidity of precipitation; and second, to restore the health of aquatic life in the lakes and ponds of the Adirondacks that is alleged to have been adversely affected by lake acidity. Data for the relationship between red spruce decline on Camel’s Hump Mountain and anthropogenic SO2 emissions or rain acidity are not presented in this study because of the historical nature of this issue and in view of the overriding effect of the drought of the 1960s in Vermont on forest health (NAPAP, 1987) (NAPAP, 1991) (Siccama, 1982). From 1960 to 1969 the state of Vermont suffered its most severe drought on record as of 1989 (USGS, 1989) and the data show that the observed decline in red spruce on Camel’s Hump in the 1970s and 1980s is a singular event that can be traced to this drought. Since then, the health of the high elevation forest on Camel’s Hump Mountain has been generally improving and not declining (Johnson A. , 1983) (Siccama, 1982) (NAPAP, 1987). Adverse effects on crops and on human health were originally suspected but these were never confirmed and are not a serious concern in the current state of the assessment of adverse effects of acid precipitation (NAPAP, 1987) (NAPAP, 1991). Accordingly, in this study we address the more unsettled question regarding the relationships among the acidity of precipitation in NY, the acidity of aquatic ecosystems in the Adirondacks, and anthropogenic SO2 emissions in a relevant geographical extent that can be described in terms of EPA Regions (EPA, 2016). We use publicly available secondary data from the sources listed in Section 2 of the paper to present an empirical test of the effect of anthropogenic SO2 emissions on the SO4 acidity of precipitation in NY and on the SO4 acidity of lakes in the Adirondacks and the effect of SO4 acidity of precipitation in NY on the SO4 acidity of lakes and ponds in the Adirondacks. Detrended correlation analysis is used to extract correlations at an annual time scale among these variables. The findings are summarized in Figure 13. The first row in Figure 13 is marked “CORR”. It shows that the correlations among the source data are very high and well over 90% in all cases. For detrended correlation analysis at an annual time scale, these correlations may be described as being derived from two sources and they are (1) a year to year responsiveness of the theoretical effect variable to the theoretical cause variable and (2) a shared and perhaps incidental long term drift in time that cannot be interpreted in terms of causation. The second row marked “DET CORR” contains the correlations at an annual time scale that survives after the long term trends in the data are removed. These detrended correlations are tested for statistical significance and where possible they are interpreted in terms of causation hypotheses at an annual time scale.
    The columns marked “EMIS-RAIN” contain hypothesis tests for the effect of anthropogenic SO2 emissions (EMIS) in four different geographical extents on the SO4 acidity of precipitation in NY (RAIN). Very high detrended correlations are observed for SO2 emissions in EPA Regions 1, 2, and 3 and EPA Regions 1, 2, 3, and 4. Both of these correlations are found to be statistically significant at α=0.001 per comparison. We conclude that the data provide sufficient evidence that the SO4 acidity of precipitation in NY is responsive to anthropogenic SO2 emissions in a large geographical area identified by the indicated EPA regions (Figure 3). In the column marked EMIS-RAIN we test the hypothesis that theSO4 acidity of lakes in the Adirondacks is responsive to the SO4 acidity of precipitation in NY on an annual time scale. The test failed. The observed detrended correlation in the sample is too low to be generalized beyond the sample data. We conclude that the data do not contain evidence of a relationship between the acidity of lakes in the Adirondacks and the acidity of precipitation in NY. This result is consistent with previous research which ascribes changes in lake acidity to the acidity of the soil in the catchment area of the lakes and not to acidity of precipitation because lakes derive an insignificant portion of their water from direct rainfall. The acidity of the soil derives from other sources including vegetation and therefore lake acidity is unlikely to be responsive to rain acidity (Krug, 1989) (NAPAP, 1987) (Wildavsky, 1997) (Munton, 2011) (Brookes, 1989) (Reville, 2008).
    However, it is known that SO2 emissions fall back to the surface not only in the form of acid precipitation but also in dry sulfate form independent of precipitation. “Dry deposition” of this form may affect both soil and lake acidity directly without the intermediation of acid precipitation (Delmelle, 2001) (Driscoll, 2001) (Driscoll, 2003) (Cosby, 1985). This hypothesis is tested for four geographical extents in the columns marked “EMIS-LAKE” (Figure 13). No statistically significant correlation is found but it is noted that the pvalue of p=0.00353 for the geographical extent of emissions defined as EPA Regions 1, 2, and 3 is very close to α=0.001 and that therefore a failure to reject H0 may imply insufficient statistical power. We conclude that the data do not provide sufficient evidence that dry deposition of sulfates due to anthropogenic SO2 emissions in EPA Regions 1, 2, and 3 can explain SO4 acidity of lakes in the Adirondacks with the caveat that greater statistical power may yield different results. It is also possible that the absence of the expected effects of anthropogenic SO2 emissions at an annual time scale may be due to the effects of natural emissions of SO2 from volcanoes and geothermal vents that have not been taken into account (Kazahaya, 2004) (Malinconico, 1987) (McGee, 2010) (Sutton, 2003) (Symonds, 1990) (Wallace, 1994) (Young, 1998). These emissions don’t occur on a continuous year-to-year basis but sporadically and randomly. Yet, they account for more than two thirds of SO2 emissions globally (HSDB, 2016). It may be difficult to detect the impact of the much lower anthropogenic emissions on an annual time scale in a context in which the larger natural flows are excluded in the analysis possibly due to insurmountable measurement issues.
  8. EVALUATION OF THE ACID RAIN PROGRAM: In view of the above, our overall evaluation of the Acid Rain Program is that: (1) The Program coincides with a corresponding increase in the rate of decline of SO2 emissions from coal fired power plants in the USA. We therefore conclude that the program has been effective in reducing anthropogenic SO2 emissions in the targeted EPA Regions. (2) The abatement of anthropogenic SO2 emissions noted in item 1 above has reduced the SO4 acidity of precipitation in NY at an annual time scale. (3) There is no evidence that the reduction of the SO4 acidity of precipitation in NY has had a measurable effect on the SO4 acidity of lakes in the Adirondacks. (4) The reduction of anthropogenic SO2 emissions noted in item 1 above may have reduced the SO4 acidity of lakes in the Adirondacks that can be attributed to dry deposition of sulfates independent of acid precipitation; but no clear indication of that effect could be found at an annual time scale for the sample period 1992-2015 used in this study. (5) It is not possible to evaluate the Acid Rain Program in terms of health of the high altitude boreal forest on Camel’s Hump Mountain in Vermont because of the much stronger effect of the drought of 1960-1969. (6) The evaluation of the success of emissions trading systems must be based not only on the basis of abatement of emissions but also on the basis of whether the environmental objectives that served as the rationale for the reduction of emissions have been achieved. (7) The study of the environmental impact of SO2 emissions suffers from a data availability bias (Das, 1998) because it relies entirely on anthropogenic emissions that are easy to measure and ignores much larger natural flows that are difficult to measure and impossible to quantify on an annual basis. All data and computational details used in this study are available in an online data archive (Munshi, SO2-Part1-Archive, 2016). Two additional installments of this research are planned. They involve the evaluation of the SO2 emissions trading system and its application in the area of climate change.

 

 

[LIST OF POSTS ON THIS SITE]

 

 

REFERENCES

  1. ALSC. (2016). ALTM. Retrieved 2016, from ALSC: http://www.adirondacklakessurvey.org/
  2. Bandow, D. (1996). Environmentalism: The Triumph of Politics. Retrieved 2016, from Action Institute: http://www.acton.org/pub/religion-liberty/volume-8-number-3/environmentalism-triumph-politics
  3. Beamish, R. (1972). Acidification of the La Cloche Mountain Lakes, Ontario, and resulting fish mortalities. Journal of the Fisheries Board of Canada, 29.8 (1972): 1131-1143.
  4. Bowley, A. (1928). The standard deviation of the correlation coefficient. Journal of the American Statistical Association, 31-34.
  5. Brookes, W. (1989, September). The continuing mythology about acid rain. Human Events, pp. 12-13.
  6. Cape, J. (1993). Direct damage to vegetation caused by acid rain and polluted cloud: definition of critical levels for forest trees. Environmental pollution, 82.2 (1993): 167-180.
  7. Chan, G. (2012). The SO2 allowance-trading system and the Clean Air Act Amendments of 1990: reflections on 20 years of policy innovation. National Tax Journal , 65.2 (2012): 419-453.
  8. Chatfield, C. (1989). The Analysis of Time Series: An Introduction. NY: Chapman and Hall/CRC.
  9. Coen, L. (2000). Developing success criteria and goals for evaluating oyster reef restoration: ecological function or resource exploitation? Ecological Engineering, 15.3 (2000): 323-343.
  10. Cole, D. (1999). When is Command-and-Control Efficient-Institutions, Technology, and the Comparative Efficiency of Alternative Regulatory Regimes for Environmental Protection. Wisconsin Law Review, (1999): 887.
  11. Conniff, R. (2009). The Political History of Cap and Trade. Retrieved 2016, from Smithsonian Magazine: http://www.smithsonianmag.com/air/the-political-history-of-cap-and-trade-34711212/
  12. Cosby. (1985). Modeling the effects of acid deposition: assessment of a lumped parameter model of soil water and streamwater chemistry. Water Resources Research, 21.1 (1985): 51-63.
  13. Cosby, B. (1985). Modeling the Effects of Acid Deposition: Estimation of Long‐Term Water Quality Responses in a Small Forested Catchment. Water Resources Research, 21.11 (1985): 1591-1601.
  14. Cowling, E. (1982). Acid precipitation in historical perspective. Environmental science & technology , 16.2 (1982): 110A-123A.
  15. Cowling, E. (1990). Acid rain and other airborne pollutants: Their human causes and consequences. Population and Development Review, 16 (1990): 205-220.
  16. Dales, J. (1968). Pollution, property, and prices: An essay in policy-making and economics. Toronto: University of Toronto Press.
  17. Das, S. (1998). Earnings predictability and bias in analysts’ earnings forecasts. Accounting Review, (1998): 277-294.
  18. Delmelle, P. (2001). Dry deposition and heavy acid loading in the vicinity of Masaya Volcano, a major sulfur and chlorine source in Nicaragua. Environmental science & technology, 35.7 (2001): 1289-1293.
  19. Driscoll, C. (2001). Acidic Deposition in the Northeastern United States: Sources and Inputs, Ecosystem Effects,. BioScience, 51.3 (2001): 180-198.
  20. Driscoll, C. (2003). Chemical response of lakes in the Adirondack region of New York to declines in acidic deposition. Environmental Science & Technology, 37.10 (2003): 2036-2042.
  21. Ellerman. (2000). Markets for clean air: The US acid rain program. Cambridge: Cambridge University Press.
  22. Ellerman, A. (2002). The temporal efficiency of SO2 emissions trading. Cambridge, MA: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=337142.
  23. EPA. (2001). Trading Programs. Retrieved 2016, from EPA: https://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE-0216B-07.pdf/$file/EE-0216B-07.pdf
  24. EPA. (2016). EPA. Retrieved 2016, from Clean Air Markets: https://www.epa.gov/airmarkets
  25. EPA. (2016). EPA Regions. Retrieved 2016, from EPA: https://www3.epa.gov/scram001/guidance_cont_regions.htm
  26. EPA-AMPD. (2016). Air Markets Program Data. Retrieved 2016, from EPA: https://ampd.epa.gov/ampd/
  27. Ferdinand, M. (2015). Less is More. Retrieved 2016, from IETA: http://www.ieta.org/resources/Resources/GHG_Report/2015/Articles/Less_is_More_EDimantchev_MFerdinand.pdf
  28. Garland, C. (1988). Acid Rain Over the United States and Canada: The DC Circuit Fails to Provide Shelter Under Section 115 of the Clean Air Act While State Action Provides a Temporary Umbrella. BC Envtl. Aff. L. Rev., 16 (1988): 1.
  29. Graedel, T. (1989). The changing atmosphere. Scientific American, (1989): 58-68.
  30. Halbert, G. (1977). 1977 Amendments to the Clean Air Act. The Journal of Law, Medicine & Ethics, 5.4 (1977): 9-9.
  31. Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6:2:65-70.
  32. HSDB. (2016). Hazardous Substances Data Bank. Retrieved 2016, from NIH.GOV: https://www.nlm.nih.gov/pubs/factsheets/hsdbfs.html
  33. Irvine, R. (1990). Requiem for acid rain. Retrieved 2016, from AIM Report: http://www.aim.org/publications/aim_report/1990/10a.html
  34. Irving, P. (1981). Productivity of field-grown soybeans exposed to acid rain and sulfur dioxide alone and in combination. Journal of Environmental Quality, 10.4 (1981): 473-478.
  35. Jenkins, J. (2009). Cap and Trade Worked for Acid Rain, Why Not for Climate Change? Retrieved 2016, from Breakthrough: http://thebreakthrough.org/archive/cap_and_trade_worked_for_acid
  36. Johnson, A. (1983). Red spruce decline in the northeastern US: hypotheses regarding the role of acid rain. Journal of the Air Pollution Control Association, 33.11 (1983): 1049-1054.
  37. Johnson, V. (2013). Revised standards for statistical evidence. Retrieved 2015, from Proceedings of the National Academy of Sciences: http://www.pnas.org/content/110/48/19313.full
  38. Joskow, P. (1998). The market for sulfur dioxide emissions. American Economic Review, (1998): 669-685.
  39. Kazahaya, K. (2004). Gigantic SO2 emission from Miyakejima volcano, Japan, caused by caldera collapse. Geology, 32.5 (2004): 425-428.
  40. Keith, L. (1983). Principles of environmental analysis. Analytical chemistry, 55.14 (1983): 2210-2218.
  41. Krug, E. (1989). Assessment of the theory and hypotheses of the acidification of watersheds. Washington DC: US Department of Energy.
  42. Langner, J. (1991). A global three-dimensional model of the tropospheric sulfur cycle. Journal of Atmospheric Chemistry, 13.3 (1991): 225-263.
  43. Larssen, T. (2000). Acid rain and acidification in China: the importance of base cation deposition. Environmental pollution, 110.1 (2000): 89-102.
  44. Lee, C. (2011). SO2 emissions and lifetimes: Estimates from inverse modeling using in situ and global, space‐based (SCIAMACHY and OMI) observations. Journal of Geophysical Research: Atmospheres, 116.D6 (2011).
  45. Lehr, J. (1992). Rational Readings on Environmental Concerns. NY: John Wiley & Sons.
  46. Malinconico, L. (1987). On the variation of SO2 emission from volcanoes. Journal of volcanology and geothermal research, 33.1-3 (1987): 231-237.
  47. McGee, K. (2010). Emission of SO2, CO2, and H2S from Augustine Volcano, 2002-2008. US Geological Survey, No. 1769-26. US Geological Survey.
  48. Melnick, R. (2010). Regulation and the courts: The case of the Clean Air Act. Brookings Institution Press.
  49. Munshi, J. (2016). SO2-Part1-Archive. Retrieved 2016, from Google Drive: https://drive.google.com/open?id=0BxTCVvGifmvLdHNTalg1d1duVWc
  50. Munshi, J. (2016). Spurious Correlations in Time Series Data. Retrieved 2016, from ssrn.com: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2827927
  51. Munton, D. (2011). Dispelling the myths of the acid rain story. Retrieved 2016, from SourceWatch: http://www.sourcewatch.org/index.php/Dispelling_the_myths_of_the_acid_rain_story
  52. NADP. (2016). Acid Rain. Retrieved 2016, from NADP: http://nadp.sws.uiuc.edu/educ/acidrain.aspx
  53. NAPAP. (1987). The National Acid Precipitation Assessment Report to Congress. Washington DC: EPA.
  54. NAPAP. (1991). 1990 Integrated Assessment Report. (U.S.). Office of the Director, and National Acid Precipitation Assessment Program (UWashington, D.C: Office of the Director, and National Acid Precipitation Assessment Program.
  55. NAPAP. (2003). National Acid Precipitation Assessment Program Report to Congress. Washington DC: EPA.
  56. NAPAP. (2011). National Aid Precipitation Assessment Program Report to Congress 2011. Washington DC: EPA.
  57. Newbery, D. (1990). Acid rain. Economic Policy, 5.11 (1990): 297-346.
  58. Popp, D. (2003). Pollution control innovations and the Clean Air Act of 1990. Journal of Policy Analysis and Management, 22.4 (2003): 641-660.
  59. Prodobnik, B. (2008). Detrended cross correlation analysis. Physical Review Letters, 100: 084102.
  60. Ray, D. (1994). Environmental Overkill: Whatever Happened to Common Sense? NY: HarperCollins Publishers .
  61. Reville, W. (2008). What made the acid rain myth finally evaporate? Retrieved 2016, from Irish Times: http://www.irishtimes.com/news/science/what-made-the-acid-rain-myth-finally-evaporate-1.900603
  62. Russell, E. (1993). Discovery of the subtle. Humans as Components of Ecosystems. New York: Springer.
  63. Schindler, D. (1988). Effects of acid rain on freshwater ecosystems. Science, 239.4836 (1988): 149-157.
  64. Schmalensee, R. (1998). An interim evaluation of sulfur dioxide emissions trading. The Journal of Economic Perspectives, 12.3 (1998): 53-68.
  65. Schofield, C. (1976). Acid precipitation: effects on fish. Ambio, (1976): 228-230.
  66. SEDAC. (2009). Sulfur Dioxide Emissions. Retrieved 2016, from columbia.edu: http://sedac.ciesin.columbia.edu/data/set/haso2-anthro-sulfur-dioxide-emissions-1850-2005-v2-86
  67. Siccama, T. (1982). Decline of red spruce in the Green Mountains of Vermont. Bulletin of the Torrey Botanical Club, (1982): 162-168.
  68. Siegfried, T. (2010). Odds Are, It’s Wrong. Retrieved 2016, from Science News: https://www.sciencenews.org/article/odds-are-its-wrong
  69. Stavins, R. (1998). What can we learn from the grand policy experiment? Lessons from SO 2 allowance trading. The Journal of Economic Perspectives, 12.3 (1998): 69-88.
  70. Stavins, R. (2012). The US sulphur dioxide cap and trade programme and lessons for climate policy. Retrieved 2016, from Vox CEPR Policy Portal: http://voxeu.org/article/lessons-climate-policy-us-sulphur-dioxide-cap-and-trade-programme
  71. Sutton, A. (2003). Lava-effusion rates for the Pu’u’O’o–Kupaianaha eruption derived from SO2 emissions and very low frequency (VLF) measurements. US Geolofical Survey, 1676 (2003): 137-148.
  72. Symonds, R. (1990). Evaluation of gases, condensates, and SO2 emissions from Augustine volcano, Alaska: the degassing of a Cl-rich volcanic system. Bulletin of Volcanology, 52.5 (1990): 355-374.
  73. Taylor, M. (2005). Regulation as mother of innovation: the case of SO2 control. Law and Policy, 27.2 (2005): 348-378.
    USGS. (1989). U.S. Geological Survey Water-Supply Paper 2375 by Jon Denner. Retrieved 1989, from USGS: http://md.water.usgs.gov/publications/wsp-2375/vt/
  74. Vogelmann, J. (1985). Forest decline on Camels Hump, Vermont. Bulletin of the Torrey Botanical Club, (1985): 274-287.
  75. Vogelmann, J. (1988). Assessing forest damage in high-elevation coniferous forests in Vermont and New Hampshire using Thematic Mapper data. Remote Sensing of Environment, 24.2 (1988): 227-246.
  76. Wallace, P. (1994). Magmatic vapor source for sulfur dioxide released during volcanic eruptions: evidence from Mount Pinatubo. Science, 265.5171 (1994): 497-499.
  77. Waxman, H. (1991). Overview of the Clean Air Act Amendments of 1990. Environmental Letters, 21 (1991): 1721.
  78. Wildavsky, A. (1997). But is it true? Harvard University Press: Cambridge, MA.
  79. Winter, S. (2001). Motivation for compliance with environmental regulations. Journal of Policy Analysis and Management, 20.4 (2001): 675-698.
  80. Young, S. (1998). Monitoring SO2 emission at the Soufriere Hills Volcano: Implications for changes in eruptive conditions. Geophysical Research Letters, 25.19 (1998): 3681-3684.

 

 

 

2 Responses to "ACID RAIN: LAKE ACIDITY IN THE ADIRONDACKS"

[…] COMMAND AND CONTROL REGULATION VERSUS EMISSIONS TRADING [LINK]  […]

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: