Australia's first national level quantitative environmental justice

Download Australia's first national level quantitative environmental justice

Post on 12-Feb-2017




1 download

Embed Size (px)


<ul><li><p>This content has been downloaded from IOPscience. Please scroll down to see the full text.</p><p>Download details:</p><p>This content was downloaded by: donnalisagreen</p><p>IP Address:</p><p>This content was downloaded on 22/04/2014 at 01:00</p><p>Please note that terms and conditions apply.</p><p>Australias first national level quantitative environmental justice assessment of industrial air</p><p>pollution</p><p>View the table of contents for this issue, or go to the journal homepage for more</p><p>2014 Environ. Res. Lett. 9 044010</p><p>(</p><p>Home Search Collections Journals About Contact us My IOPscience</p><p></p></li><li><p>Environmental Research Letters</p><p>Environ. Res. Lett. 9 (2014) 044010 (10pp) doi:10.1088/1748-9326/9/4/044010</p><p>Australias first national level quantitativeenvironmental justice assessment ofindustrial air pollutionJayajit Chakraborty1 and Donna Green2,3</p><p>1 School of Geosciences, University of South Florida, Tampa, FL 33620, USA2 Climate Change Research Centre and the ARC Centre of Excellence for Climate System Science,University of New South Wales, Sydney, NSW 2052, Australia</p><p>E-mail: and</p><p>Received 15 January 2014, revised 16 March 2014Accepted for publication 17 March 2014Published 11 April 2014</p><p>AbstractThis study presents the first national level quantitative environmental justice assessment ofindustrial air pollution in Australia. Specifically, our analysis links the spatial distribution ofsites and emissions associated with industrial pollution sources derived from the NationalPollution Inventory, to Indigenous status and social disadvantage characteristics ofcommunities derived from Australian Bureau of Statistics indicators. Our results reveal a clearnational pattern of environmental injustice based on the locations of industrial pollutionsources, as well as volume, and toxicity of air pollution released at these locations.Communities with the highest number of polluting sites, emission volume, andtoxicity-weighted air emissions indicate significantly greater proportions of Indigenouspopulation and higher levels of socio-economic disadvantage. The quantities and toxicities ofindustrial air pollution are particularly higher in communities with the lowest levels ofeducational attainment and occupational status. These findings emphasize the need for moredetailed analysis in specific regions and communities where socially disadvantaged groups aredisproportionately impacted by industrial air pollution. Our empirical findings also underscorethe growing necessity to incorporate environmental justice considerations in environmentalplanning and policy-making in Australia.</p><p>Keywords: environmental justice, Australia, quantitative, industrial air pollution</p><p>1. Introduction</p><p>The disproportionate distribution of environmental goodsand bads in relation to the ethnic or socio-economic sta-tus of nearby communities has been well-established in theinternational literature through the use of an environmentaljustice framework, as previously noted in a special editionof this journal (Stephens 2007). Environmental injustice isdefined broadly as the unequal distribution of environmental</p><p>3 Author to whom any correspondence should be addressed.Content from this work may be used under the terms ofthe Creative Commons Attribution 3.0 licence. Any further</p><p>distribution of this work must maintain attribution to the author(s) and thetitle of the work, journal citation and DOI.</p><p>risks and benefits, with the burden of the risks and the dearth ofthe benefits falling mainly on racial and/or ethnic minorities,low-income populations, and other socially disadvantagedindividuals.</p><p>The United Church of Christs Commission for RacialJustice (UCC 1987) provided the first comprehensive nationallevel analysis of racial, ethnic and economic inequities inthe distribution of environmental hazards in the US. Usingzip-code level data, this study found the presence of com-mercial hazardous waste facilities and uncontrolled wastesites to be significantly associated with a higher percentageof the racial minority population, lower household incomeand lower housing values across the nation. These findingswere investigated and confirmed by numerous studies that</p><p>1748-9326/14/044010+10$33.00 1 c 2014 IOP Publishing Ltd</p><p></p></li><li><p>Environ. Res. Lett. 9 (2014) 044010 J Chakraborty and D Green</p><p>provided empirical support regarding the widespread practiceof locating polluting industries in low-income and non-whiteneighborhoods (Bullard 1990, Bryant and Mohai 1992, Brown1995, Mohai et al2009b, Schlosberg and Carruthers 2010).</p><p>These case studies, and related evidence, led to theimplementation of policies at the national, state and locallevel, including an Executive Order issued by President Clintonin 1994 that required environmental justice concerns to beconsidered in the decision-making processes for industrialactivities that would significantly affect the environment. By2007, the US Office of Environmental Justice had distributedmore than 800 grants to local groups working to improveenvironmental justice outcomes. These groups started theirown pollution assessments to confirm industry emission datathrough low cost, but certifiable, citizen science activities suchas the Bucket Brigades (LABB, no date, Sandler and Pezzullo2007). In less than three decades, environmental justice hasgone from being a fledgling research field to a mainstreamand necessary component of US environmental planning andpolicy.</p><p>In significant contrast to the activities in the US, thereexists no comprehensive quantitative analysis that drawstogether these environmental and social justice concerns atthe national level in Australia (Arcioni and Mitchell 2005,Byrne and MacCallum 2013, Lloyd-Smith and Bell 2003).This is despite an obvious and growing need for such researchto occur, with a number of well-documented sites of massiveindustrial pollution that have disproportionately affectedindividuals of lower socio-economic status and Indigenouscommunitiessuch as mining and smelting emissions inMt Isa (Mackay et al2013, Munksgaard et al2010, Taylorand Schniering 2010) and Port Pirie (EDO 2012, McMichaelet al1986, Taylor et al2013). This is not just an historic issue,since similar concerns are being raised about decisions tolocate future toxic sites, such as the planned radioactive wastedump on Aboriginal land at Muckaty Station in the NorthernTerritory (EJS, no date, Millner 2011).</p><p>The analysis herein addresses this research gap by pre-senting the first national assessment of spatial and socialinequalities in the distribution of industrial air pollution inAustralia. This research integrates air emissions data from theNational Pollutant Inventory (NPI) for the period 20112012with information on the Indigenous status of the populationand social disadvantage indices derived from the AustralianBureau of Statistics (ABS) 2011. Our study seeks to determinewhether socially disadvantaged populations are dispropor-tionately proximate to industrial air pollution. This approachdeliberately mirrors the US methods and analysis that use theToxic Release Inventory (TRI) and socio-demographic censusdata, in order to facilitate a consideration of the Australiancase alongside existing US studies (Howes 2001). To providea framework for this national level Australian assessment,we focus on the relationship between the extent of socialdisadvantage and four specific indicators of industrial airpollution. These include: (a) the presence/absence of NPI sitesemitting air pollutants; (b) the number of NPI sites emittingair pollutants; (c) the total volume of air emissions from NPIsites; and (d) the toxicity-weighted volume of air pollution,based on the NPI toxicity rating (NEPC 1999, appendix III),released from NPI sites.</p><p>2. Data and methods</p><p>2.1. Air pollution data</p><p>Air pollution data for this study comes from the most recentset of industry supplied estimates provided to the NationalPollution Inventory (NPI 2013). Of the entire set of toxicreleases available from the NPI (i.e. to air, water and land), wechose to focus on airborne emissions for two reasons. First,atmospheric emissions represent the majority of all releasedchemicals in the NPI. Second, emissions to air are most likelyto result in actual human exposure and least dependent onhuman behaviors for exposure to occur (Daniels and Friedman1999, National Research Council 1991).</p><p>The NPI is a joint Commonwealth-State program that hasprovided open-access estimates of toxic emissions data fromgovernment and industrial sources since 2000. Initially theinventory was modeled on the US TRI, although the range ofincluded pollutants was somewhat smaller. The NPI TechnicalAdvisory Panel final report (NEPC 1999) suggested an initiallist of 36 substances. It was later expanded to the current list of90 substances, which remains a significantly smaller numberthan the 682 on the TRI (TRI 2013).</p><p>The NPI allocates a toxicity rating for each chemicalbased on its impact on human health, its impact on theenvironment and the risk to its exposure, in order to rankpollutants and select the most important ones for furtherconsideration (NEPC 1999). The downloadable datasheetshosted on the NPI website provide geo-referenced data foreach emission of every chemical over a specific threshold, andan estimation of the annual emissions of each of the rankedchemicals. Emissions calculations are made by the polluterusing estimation handbooks for each chemical, which are alsohosted on the NPI website (NPI 2013). The data for this studyincluded estimations from the year 20112012.</p><p>2.2. Social disadvantage data</p><p>The potential social inequities in the distribution of industrialair pollution were analyzed using a set of variables fromthe Census of Population and Housing (ABS 2011) at theStatistical Area Level 2 (SA2). The SA2s are geographicunits with an average population of about 10 000 persons(with a range of 300025 000) that cover the entire nationwithout gaps or overlaps. With these divisions, they aim to,represent a community that interacts together socially andeconomically (ABS 2013a). To ensure stable estimates forour social disadvantage variables, we excluded 112 SA2s withvery small population counts. Our study uses the remaining2110 SA2 units where the usual resident population is morethan, or equal to, 10 persons.</p><p>We used five specific measures to capture the multipledimensions of social disadvantage. As the Indigenous Aus-tralian population is one of the most socially disadvantagedgroups in Australia (AIHW 2011), we used the percentage ofindividuals self-identifying as Aboriginal and/or Torres StraitIslander as the first indicator. To measure socio-economicstatus, an important focus of environmental justice advocacyand research, we relied on the Socio-Economic Indexes for</p><p>2</p></li><li><p>Environ. Res. Lett. 9 (2014) 044010 J Chakraborty and D Green</p><p>Table 1. Socio-economic indexes for areas (SEIFA): definitions and interpretations (Source: Australian Bureau of Statistics, 2013b.).</p><p>InterpretationIndex name Definition Low score High score</p><p>Index of relativesocio-economic disadvantage(IRSD)</p><p>Summarizes a range ofinformation about theeconomic and socialconditions of people andhouseholds within an area;only measures relativedisadvantage.</p><p>Relatively greaterdisadvantage</p><p>A relative lack ofdisadvantage</p><p>Index of relativesocio-economic advantageand disadvantage (IRSAD)</p><p>Summarizes informationabout the economic andsocial conditions of peopleand households within anarea, including both relativeadvantage and disadvantagemeasures.</p><p>Relatively greaterdisadvantage and a lackof advantage</p><p>Relative lack of disadvantageand greater advantage</p><p>Index of economic resources(IER)</p><p>Focuses on the financialaspects of relativesocio-economic advantageand disadvantage, bysummarizing variablesrelated to income and wealth.</p><p>Relative lack of access toeconomic resources</p><p>Relatively greater access toeconomic resources</p><p>Index of education andoccupation (IEO)</p><p>Designed to reflect theeducational and occupationallevel of communities.</p><p>Relatively lower educationand occupation status ofpeople.</p><p>Relatively higher educationand occupation status ofpeople.</p><p>Areas (SEIFA)a suite of four indexes updated each censusby the ABS to rank geographic areas according to their relativesocio-economic advantage and disadvantage (ABS 2013b).For each SEIFA index, every SA2 is given a SEIFA score thatmeasures how relatively advantaged or disadvantaged thatarea is compared with the other areas.</p><p>While several specific individual variables (e.g., annualincome, poverty rate and median housing value) have beenused in the environmental justice research literature to assessthe socio-economic status of communities, each SEIFA indexrepresents a summary measure that focuses on one particu-lar dimension of socio-economic disadvantage/advantage andencompasses a range of relevant census variables. The defi-nitions of the SEIFA indexes used in this study are providedin table 1. Each index score is a weighted combination ofmultiple variables from the 2011 census, and is constructedusing principal components analysis (ABS 2013b).</p><p>2.3. Methods</p><p>To determine how air pollution is related to social disadvantagedata on NPI sites and their emission-related attributes werespatially aggregated to each of the 2110 SA2 areas representingour units of analysis. It is also important to factor in the NPIemission sites that are located near the boundaries of the SA2hosting them. This is often referred to as the edge effectproblem in environmental justice research (Bolin et al2002,Chakraborty et al2011) and occurs when a polluting industryis so close to the edge or boundary of the host census unit thata neighboring (non-host) census unit is also exposed to the airpollution. To address this issue, all NPI sites and emissionslocated within 1 km of each SA2 boundary were included</p><p>in the air pollution-related estimates at the SA2 level. Bufferdistances of 1 km (note: common practice is to use 1 mile inUS studies) have been used in a large number of environmentaljustice studies to estimate the areal extent of exposure toair pollutants (Baden and Coursey 2002, Bolin et al2002,Boone 2002, Chakraborty and Armstrong 1997, Glickman1994, Kearney and Kiros 2009, Maantay 2007, Mennis andJordan 2005, Mohai et al2009a, Neumann et al1998, Walkeret al2005).</p><p>Our statistical analysis comprised of three phases. Wefirst examined the presence or absence of sites that reportair pollution emissions of the most toxic 90 chemicals (theidentified...</p></li></ul>