Integrating site-specific dispersion modeling into life cycle assessment, with a focus on inhalation risks in chemical production

Figures & data

Table 1. Existing LCIA methods/models for assessing human health impact.

LCIA method/Human health characterization model	Last update to human health CFs	Level of regionalization
TRACI 2/USEtox (Bare 2011)	2016	USEtox divides the world into 24 regions* and provides regionalized environmental landscape parameters for each region.
CML/USEtox (Rosenbaum et al. 2008, Rosenbaum et al. 2011)	2010
ReCiPe/USES-LCA 2.0 (Zelm, Huijbregts, and Meent 2009)	2015	USES-LCA 2.0 provides default environmental landscape parameters at three geographical scales (global, continental, and urban). ReCiPe provides different CFs based on “archetype LCIA” such as high vs. low population density areas and high vs. very high stress watersheds.
IMPACT North America (Humbert et al. 2009)	2013	IMPACT North America divides the United States and Canada into 1° × 1° air cells, 523 watersheds, and five coastal zones. Within each cell or zone, the “archetype LCIA” is used to differentiate high vs. low population density area and high vs. low agricultural production regions.
GLOBOX (Wegener Sleeswijk and Heijungs 2010)	2011	GLOBOX divides the world into 250 regions and provides default environmental landscape parameters.

Notes. CF = characterization factor.

*With overlap (e.g., North America vs. USA and southern Canada).

Table 2. Classification of unit processes (based on ACC LCI; American Chemistry Council 2011) .

Model scenario	Unit process	HAPs emitted	Total no. of plants*
Site-specific dispersion modeling (Exact location is known)	Cl2 and NaOH	Benzene, CCl4, Cl2, Pb, and Hg(II)	14
	Aniline	Pb	5
	Pyrolysis gas (olefins)	Cl2	3
	Benzene	Cl2	16
	MDA/MDI	Cl2, formaldehyde, methanol, Cl2, and CCl4	4
Non-site-specific multimedia modeling (Exact location is unknown)	Crude oil production and processing	As(V), benzene, Cl2, Cr(VI), ethyl benzene, ethylene dibromide, Hg(II), Ni(II), PAH as B(a)P, Sb(V), toluene and xylene	N/A
	Natural gas production and processing
	Salt mining
Not modeled	Ammonia	No HAP emissions reported at the manufacturing site	N/A
	Methanol
	Hydrogen
	Carbon monoxide

*Total number of plants that were included for site-specific modeling that covers 85% of the annual production capacity.

Figure 1. The system boundary of cradle-to-gate MDI production (modified from American Chemistry Council 2011).

Table 3. Unit processes and site-specific modeling/average stack parameters (EPA 1999a) .

	Average stack parameters
Unit process	Height (m)	Diameter (m)	Exit velocity (m/sec)	Exit temperature (K)
Cl2 and NaOH	10.68	0.92	8.94	318.61
Aniline	16.73	1.17	8.20	399.73
Pyrolysis gas (olefins)	25.10	1.31	4.75	409.72
Benzene	14.67	0.23	0.31	297.13
MDA/MDI	5.87	0.12	1.00	315.28

Figure 2. Census tract–level inhalation risks of site-specific unit processes (left: cancer risk; right: noncancer HI).

Figure 3. County-level average inhalation risks of site-specific unit processes (left: cancer risk; right: noncancer hazard index).

Figure 4. Distribution of inhalation risks associated with site-specific unit processes at the county level (left: cancer risk; right: noncancer hazard index).

Table 4. Production capacities of chemical plants in relatively high risk areas.

Area	No. of plants	Production capacities by mass
		Aniline	Benzene	Cl2/NaOH	Olefins	MDI
Houston	10	18.1%	37.1%	26.5%	48.2%	43.5%
Baton Rouge	7	55.3%	0%	6.0%	46.3%	56.5%
Sum	17	73.4%	37.1%	32.5%	94.5%	100%

Figure 5. Site-specific plant locations and high cancer risk areas.

Figure 6. Site-specific plant locations and high noncancer hazard index areas.

Table 5. Inhalation risks of unit processes without exact location (HAPs emitted to the continental air compartment).

Environmental compartment	Volume (m^3)	Cancer risk	Noncancer HI
Urban air	5.76 × 10^10	4.42 × 10^−10	4.46 × 10^−6
Continental air	1.00 × 10^16	4.61 × 10^−10	4.65 × 10^−6
Global air	4.60 × 10^17	2.13 × 10^−11	1.52 × 10^−7

Figure 7. Inhalation risks by HAPs for non-site-specific unit processes.

Table 6. County-level inhalation risk statistics (AERMOD).

Risk level	Cancer Risk	Noncancer HI
Maximum	1.70 × 10^−9	1.54 × 10^−3
Median	1.84 × 10^−12	5.36 × 10^−5
Minimum	5.30 × 10^−14	1.12 × 10^−6

Table 7. Inhalation risks of site-specific unit processes (if using USEtox) (assuming that HAPs were emitted to the urban air compartment).

Environmental compartment	Cancer risk	Noncancer HI
Urban air	1.99 × 10^−9	5.42 × 10^−4
Continental air	1.14 × 10^−12	8.98 × 10^−8
Global air	3.25 × 10^−13	1.64 × 10^−9

Table 8. Inhalation risks of non-site-specific unit processes (assuming that HAPs were emitted to the urban air compartment).

Environmental compartment	Cancer risk	Noncancer HI
Urban air	1.83 × 10^−6	2.32 × 10^−2
Continental air	4.60 × 10^−10	4.62 × 10^−6
Global air	2.13 × 10^−11	1.52 × 10^−7

Figure 8. Relative contributions of unit processes to inhalation risks.

Table 9. Mass distributions of HAPs in different environmental compartments.

HAP	Air compartment (%)	Water compartment(%)	Soil compartment (%)
As(V)	4.81 × 10^−3	6.57	93.4
Benzene	89.2	10.7	5.59 × 10^−3
Cr(VI)	4.41 × 10^−2	33.8	66.2
Ethyl benzene	98.0	1.88	0.152
Ethylene dibromide	72.1	27.5	0.484
Hg(II)	7.23 × 10^−4	7.39 ×10^−2	99.9
Ni(II)	6.53 × 10^−5	33.4	66.6
PAH as B(a)P	1.03	11.5	87.4
Sb(V)	2.30 × 10^−2	46.9	53.1
Toluene	97.4	2.47	0.127
Xylene	97.6	2.12	0.256

Notes. HAPs with the majority of the mass distributed in the air compartment at steady state are in bold.

Bare, J. 2011. TRACI 2.0: The tool for the reduction and assessment of chemical and other environmental impacts 2.0. Clean Technol. Environ. Policy 13 (5):687–696. doi:10.1007/s10098-010-0338-9.

 Web of Science ®Google Scholar

Rosenbaum, R. K., T. Bachmann, L. Gold, M. J. Huijbregts, O. Jolliet, R. Juraske, A. Koehler, H. Larsen, M. MacLeod, M. Margni, T. McKone, J. Payet, M. Schuhmacher, D. Meent, and M. Hauschild. 2008. USEtox—The UNEP-SETAC toxicity model: Recommended characterisation factors for human toxicity and freshwater ecotoxicity in life cycle impact assessment. Int. J. Life Cycle Assess. 13 (7):532–546. doi:10.1007/s11367-008-0038-4.

 Web of Science ®Google Scholar

Rosenbaum, R. K., M. J. Huijbregts, A. Henderson, M. Margni, T. McKone, D. Meent, M. Hauschild, S. Shaked, D. Li, L. Gold, and O. Jolliet. 2011. USEtox human exposure and toxicity factors for comparative assessment of toxic emissions in life cycle analysis: Sensitivity to key chemical properties. Int. J. Life Cycle Assess. 16 (8):710–727. doi:10.1007/s11367-011-0316-4.

 Web of Science ®Google Scholar

Zelm, R., M. J. Huijbregts, and D. Meent. 2009. USES-LCA 2.0—A global nested multi-media fate, exposure, and effects model. Int. J. Life Cycle Assess. 14 (3):282–284. doi:10.1007/s11367-009-0066-8.

 Web of Science ®Google Scholar

Humbert, S., R. Manneh, S. Shaked, C. Wannaz, A. Horvath, L. Deschenes, O. Jolliet, and M. Margni. 2009. Assessing regional intake fractions in North America. Sci. Total Environ. 407 (17):4812–4820. doi:10.1016/j.scitotenv.2009.05.024.

 PubMed Web of Science ®Google Scholar

Wegener Sleeswijk, A., and R. Heijungs. 2010. GLOBOX: A spatially differentiated global fate, intake and effect model for toxicity assessment in LCA. Sci. Total Environ. 408 (14):2817–2832. doi:10.1016/j.scitotenv.2010.02.044.

 PubMed Web of Science ®Google Scholar

American Chemistry Council. 2011. Cradle-to-gate life cycle inventory of nine plastic resins and four polyurethane precursors. Washington, DC: American Chemistry Council.

 Google Scholar

U.S. Environmental Protection Agency. 1996. Technology transfer network: 1996 national-scale air toxics assessment - Unit Risk Estimate (URE). Accessed March 21, 2018. https://archive.epa.gov/airtoxics/nata/web/html/gloadd.html.

 Google Scholar