<p> 1ELECTRONIC SUPPLEMENTARY MATERIAL FOR 2 3LCIA OF IMPACTS ON HUMAN HEALTH AND ECOSYSTEMS (USEtox) 4 5USEtox fate and ecotoxicity factors for comparative assessment of toxic emissions in Life Cycle Analysis: 6Sensitivity to key chemical properties 7 8Andrew D. Henderson • Michael Z. Hauschild • Dik van de Meent • Mark A. J. Huijbregts • Henrik Fred Larsen 9• Manuele Margni • Thomas E. McKone • Jerome Payet • Ralph K. Rosenbaum • Olivier Jolliet 10 11Received: 30 November 2010 / Accepted: 28 March 2011 12© Springer-Verlag 2011 13 14A. D. Henderson () • O. Jolliet 15Department of Environmental Health Sciences, School of Public Health, University of Michigan, 109 South 16Observatory, Ann Arbor, Michigan, 48109, USA 17e-mail: [email protected] 18 19M. Z. Hauschild • H. F. Larsen • R. K. Rosenbaum 20Department of Management Engineering, Technical University of Denmark, Produktionstorvet, building 424, 2800, 21Lyngby, Denmark 22 23D. van de Meent • M. A. J. Huijbregts 24Department of Environmental Science, Radboud University Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The 25Netherlands 26 27D. van de Meent 28National Institute of Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands 29 30M. Margni 31CIRAIG, École Polytechnique de Montréal, 2900 Édouard-Montpetit, P.O. Box 6079, Stn. Centre-ville, Montréal 32(Québec) H3C 3A7, Canada 33 34T. E. McKone 35University of California Berkeley, and Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, 36California, 94720, USA 37 38J. Payet 39Cycleco, 1011 av. Leon Blum, 01500 Amberieu, France</p><p>1 1 40Annex S1. Environmental compartments and scales of USEtox</p><p>41</p><p>42Fig. S1 Nested structure of USEtox compartments. The global scale is modeled as a closed system,</p><p>43while transport between interior compartments occurs as a result of advection of air and water (after</p><p>44Rosenbaum et al. 2008)</p><p>45</p><p>46Table S1 Important characteristics of environmental compartments modeled in USEtox</p><p>Scale Compartment Area Height or depth Volume Residence time km2 m m3 d</p><p>Urban Air 2.450E+02 240 5.76E+10 5.38E-02</p><p>Continental Air 1.0E+07 1000 1.0E+16 1.1E+01 Fresh water 2.7E+05 2.5 6.8E+11 1.4E+02 Coastal sea water 9.8E+05 100 9.8E+13 3.6E+02 Natural soil 4.4E+06 0.1 4.4E+11 1.2E+06 Agricultural soil 4.4E+06 0.1 4.4E+11 1.2E+06</p><p>Global Air 4.6E+08 1000 4.6E+17 inf Fresh water 4.2E+06 2.5 1.1E+13 1.4E+02 Ocean water 3.2E+08 200 6.4E+16 inf Natural soil 6.8E+07 0.1 6.8E+12 1.2E+06 Agricultural soil 6.8E+07 0.1 6.8E+12 1.2E+06</p><p>2 2 47Annex S2. Freshwater ecotoxcity effect factors</p><p>48S2.1 Example calculation of HC50 and PNEC</p><p>49This section presents detailed data enabling the comparison between the average toxicity for</p><p>50freshwater species and the most sensitive species for ecotoxicity measurements for the insecticide</p><p>51malathion. All data are chronic EC50s; when several EC50s where available for the same species,</p><p>52the geometric mean is reported, as per USEtox guidelines. Ecotoxicity data were collected from 5</p><p>53international databases following the rules describes in the AMI database (Payet, 2004). </p><p>54</p><p>55Table S2.1 Detailed chronic ecotoxicity data for 16 species for 5 different phyla. When several</p><p>56EC50s are available for one species, the geometric mean is reported</p><p>Species name Phyla Species level geomean EC50 (mg/L) Daphnia magna Arthropod 5.20E-04 Hesperoperla pacifica Arthropod 5.10E-03 Pteronarcys californicus Arthropod 4.50E-02 Danio rerio Chordata 3.50E-02 Umbra pygmaea Chordata 1.40E-01 Jordanella floridae Chordata 2.35E-01 Poecilia reticulata Chordata 8.19E-01 Cyprinus carpio Chordata 1.40E+00 Carassius auratus Chordata 1.65E+00 Alburnus alburnus Chordata 1.21E+01 Anodonta cygnea Mollusca 2.25E+02 Anodonta cygnea zellensis Mollusca 2.25E+02 Anodonta anatina Mollusca 5.00E+02 Unio pictorum Mollusca 3.13E+04 Dugesia dorotocephala Nematode 1.31E+01 Raphidocelis subcapitata Plant 1.30E+01 57</p><p>58</p><p>3 3 59Following the indications given in USEtox, and in order to balance the relative weight of the</p><p>60species, intermediate weighting is carried out in order to calculate the geometric mean at the phyla</p><p>61level.</p><p>62</p><p>63Table S2.2 Geometric mean of the EC50s per phyla for chronic ecotoxicity tests for malathion</p><p>Phylum Phyla level geomean (mg/L) Arthropod 4.92E-03 Chordata 5.95E-01 Mollusca 9.43E+02 Nematode 1.31E+01 Plant 1.30E+01 64</p><p>65The HC50 is then calculating using the basis of the geometric mean of the different phyla, assuming</p><p>66a relative weight of 1 for each phylum. The PNEC is calculated by applying a safety factor of 10 to</p><p>67the chronic ecotox data for the most sensitive species. </p><p>68</p><p>69Table S2.3 Comparison between the average ecotoxicological response of species and the most</p><p>70sensitive species for measuring potential toxicity of malathion. (Numbers in parenthesis are</p><p>71described below and refer to columns indicated in Fig. 1.)</p><p>PNEC without PNEC without PNEC with All Daphnia magna & Indicator Daphnia magna species (1) Hesperoperla pacifica (2) (3) HC50 (geomean of EC50) 3.42E+00 4.29E+00 5.33E+00 Most sensitive species 5.20E-04 5.10E-03 3.50E-02 72</p><p>73(1) The total dataset of the 16 species is used to calculate the HC50, the most sensitive species</p><p>74 of the dataset is Daphnia magna.</p><p>4 4 75(2) Only 15 species of the dataset were used to calculate the HC50. Daphnia magna is removed</p><p>76 in order to highlight the influence of this species on the HC50 and of the most sensitive species.</p><p>77 In the remaining dataset, the most sensitive species is Hesperoperla pacifica.</p><p>78(3) Only 14 species were used to calculate the HC50. Daphnia magna and Hesperoperla</p><p>79 pacifica are both removed from the dataset, highlighting the influence of the two most sensitive</p><p>80 species on the calculation of the HC50.</p><p>81</p><p>82</p><p>83S2.2 PAF curve and HC50s</p><p>84</p><p>85As shown by Van Zelm et al. (2007, 2009), the slope of the PAF curve can be both highly</p><p>86dependent on the mode of action of a chemical and highly uncertain. Due to the lack of data to</p><p>87derive a slope based on non-linear considerations, a linear assumption is a pragmatic solution, and</p><p>88PAF = 0.5 is the least data-demanding and least uncertain working point (Larsen and Hauschild</p><p>892007b). The key parameter in Eq. (2) is HC50EC50. It represents the chronic hazardous concentration</p><p>90for 50% of the species included in the species sensitivity distribution and is calculated as the</p><p>91geometric mean of the single species EC50 values, with preference given to chronic test values. </p><p>92</p><p>93In USEtox, HC50s are taken preferentially from Payet (2004), which is mainly based on ECOTOX</p><p>94(http://www.epa.gov/ecotox) and IUCLID (2000). If available, chronic data are used; they are</p><p>95otherwise extrapolated from acute EC50-data by applying a best estimate acute-to-chronic ratio of</p><p>961.9 for organic substances and 2.2 for pesticides. Acute toxicity data from the RIVM e-toxBase</p><p>97(www.e-toxbase.com) were used for missing substances according to Van Zelm et al. (2007),</p><p>5 5 98applying an acute-to-chronic ratio of 2. Resulting HC50s are reported in the USEtox organic</p><p>99database for 2500 organic and 20 inorganic substances (Huijbregts et al., 2010).</p><p>100</p><p>6 6 101Annex S2 References (Supplemental to manuscript references):</p><p>102</p><p>103IUCLID (2000) IUCLID CD-ROM, Year 2000 edition. Public data on high volume chemicals</p><p>104Van Zelm R, Huijbregts MAJ, Harbers JV, Wintersen A, Struijs J, Posthuma L, van de Meent D,</p><p>105 (2007) Uncertainty in msPAF-based ecotoxicological freshwater effect factors for chemicals</p><p>106 with a non-specific mode of action in life cycle impact assessment. Integrated Environ Assess</p><p>107 Manage 3(2):203–210</p><p>108</p><p>109</p><p>7 7 110Annex S3. Tabulated results for the five selected substances</p><p>111</p><p>112Table S3 Fate parameters as calculated by USEtox for selected substances: fate factor from water,</p><p>113air and soil to water; exposure factor in water; transfer fractions from air to soil and water, and from</p><p>114soil to water</p><p>Substance FFw,w (d) FFw,a (d) FFw,s (d) XFw (-) FFww ·XFw (d) fa,w (-) fs,w (-) fa,s (-)</p><p>Acephate 39 6.5 16 1.0 39 0.16 0.40 0.18 TCDD 8.9 0.14 4.8E-3 0.12 1.1 0.015 5.4E-4 0.14 Toluene 3.9 8.0E-4 0.049 1.0 3.9 2.0E-4 0.012 2.1E-4 Triethylene glycol 19 0.94 4.5 1.0 19 0.050 0.24 0.089 Triflusulfuron 92 26 33 1.0 92 0.28 0.36 0.36 methyl 115</p><p>116</p><p>117Table S4 Calculated freshwater ecotox characterization factors of selected substances for</p><p>118emissions to water, air and soil</p><p> freshwater ecotox freshwater ecotox freshwater ecotox CFw CFa CFs Substance (PAF m3 d kg-1) (PAF m3 d kg-1) (PAF m3 d kg-1) Acephate 1.0E+02 2.5E+02 6.3E+02 TCDD 9.1E+04 3.2E+03 5.9E+06 Toluene 1.1E-02 7.0E-01 5.6E+01 Triethylene glycol 1.9E-02 9.2E-02 3.9E-01 Triflusulfuron 1.1E+04 1.5E+04 4.1E+04 methyl 119</p><p>8 8 120Annex S4. Complementary graphs</p><p>121</p><p>122Fig. S2 3073 organic substances studied represented on a log Kaw vs. log Kow, grouped according to</p><p>123half life in water</p><p>124</p><p>9 9 125</p><p>126Fig. S3 Product of fate factor and exposure factor in the freshwater compartment (FFw,w∙XFw, days)</p><p>127as a function of log Koc for 3073 organic substances on a logarithmic scale. Data are grouped</p><p>128according to the substance air-water partitioning coefficient (log Kaw). High log Koc values may not</p><p>129be directly measureable but may be estimated from other parameters, e.g., log Kow</p><p>130</p><p>131</p><p>10 10 132</p><p>133Fig. S4 Fate factor in water (d), grouped according to logKow</p><p>134</p><p>135</p><p>136</p><p>137Fig. S5 Dissolved fraction in water, grouped according to logKow</p><p>11 11 138</p><p>139</p><p>140</p><p>141Fig. S6 Product of fate factor and exposure factor from soil to the freshwater compartment (fs,w</p><p>142∙FFw,w∙XFw) as a function of log Koc for 3073 organic substances. Data are grouped according to the</p><p>143substance air-water partitioning coefficient (log Kaw)</p><p>144</p><p>12 12 145</p><p>146Fig. S7 Transfer fraction from air to soil (fa,s) as a function of log Kaw for 3073 organic substances.</p><p>147Data are labeled according to the half life of the substance in air (days)</p><p>148</p><p>149</p><p>13 13 150</p><p>151Fig. S8 Transfer fraction from air to water vs. log Kaw, grouped according to half life in air</p><p>152</p><p>14 14</p>