Academic journal article The Geographical Review

Allocating and Mapping Carbon Footprint at the Township Scale by Correlating Industry Sectors to Land Uses

Academic journal article The Geographical Review

Allocating and Mapping Carbon Footprint at the Township Scale by Correlating Industry Sectors to Land Uses

Article excerpt

Climate change primarily caused by carbon dioxide (C[O.sub.2]) concentration has been recognized as a daunting threat to international development and has attracted considerable concern worldwide (Ma and others 2015). During intergovernmental climate negotiations, the mitigation and allocation of carbon emissions have been a critical issue and crucial task for policymakers (Huang and Meng 2013). A series of mandatory allocative targets and policies to decrease and distribute overall carbon emissions have already been, or will soon be, set up by the United Nations and many developed or developing countries, for example: Brazil, China, India, Korea, U.K., and U.S.) (Ahn 2014, Huisingh and others 2015). The targets depend intensively on statistically and spatially efficient estimates (Harris and others 2012), to be in line with 'common but differential' (Miao and others 2015) principles. In widespread efforts to monitor humanity's carbon emissions, the "carbon footprint" has emerged as a key indicator in recent decades (Freidberg 2014).

As a new concept on biocapacity, "carbon footprint", rooted in "ecological footprinting" (Wackernagel and Rees 1996), is defined as "a measurement of the total amount (tonnes) of carbon dioxide emissions directly and indirectly caused by human activities" (Wiedmann and Minx 2008). It stands for not just energy consumption through fossil fuel combustion, but also ongoing waste (Wiedmann and Minx 2008). This is similar to the four key inventories --energy, industrial and product processing, land use, and waste categories--documented by the Intergovernmental Panel on Climate Change (IPCC) (Intergovernmental Panel on Climate Change 2006). The term differs from the IPCC report because of data availability and uncertainties, the inclusion of only C[O.sub.2] without regard for other greenhouse gases--C[H.sub.4], [N.sub.2]O, CO--and the narrower scope of a carbon footprint instead of a "climate footprint" (Wiedmann and Minx 2008). Notwithstanding, carbon footprint is not restrained as an area-based indicator; its total amount is calculated in mass units (kg, t, and the like) and thus no conversion to an area unit (ha, [m.sup.2], k[m.sup.2], and such) takes place (Wiedmann and Minx 2008).

With respect to current allocative approaches to carbon footprints, increasing magnitudes of existing functional measurements are focusing on two allocative perspectives: from productionist-based to consumptionist-based (Turner and others 2011; Liu and others 2015; Ormond 2015), and from global-scale (Hertwich and Peters 2009; Wei and others 2014) and regional-scale (Wang and Zhao 2015) to local-scale (Brown and others 2009; Sovacool and Brown 2010) and neighborhood-scale (Christen and others 2010; Petsch and others 2011; Kellett and others 2013).

For the first, extensive attention is given to a full life-cycle assessment (LCA), monitoring and capturing carbon emissions over the full life of a product or service, shifting from producers (production) to individuals (consumption) (Weber and Matthews 2008; Strohbach and others 2012). This is usually addressed from two directions: bottom-up process analysis (PA) and top-down environmental input-output analysis (EIOA) (Druckman and Jackson 2009; Wiedmann 2009; Larsen and Hertwich 2010). The former takes supply chains into account so as to investigate the microlevel environmental impacts of products or services from cradle to grave (Freidberg 2014; Ren and others 2015). As a technique of supply-chain governance, the power behind PA-based LCA comes from its quantitative nature, which is more comprehensive, objective, and adequate for political cooperation (Freidberg 2014). However, modeling the complete life cycle has several limitations. Aside from its restrictive assumptions (Galli and others 2012; Freidberg 2014), complex boundary problems (Wiedmann and Minx 2008), and inapplicability to the macroscale (and even the sector level; consult further difficulties of larger entities in Wiedmann and Minx 2008), the lack of reliable data has introduced large uncertainties and challenges for carbon emissions (Drouet and others 2015). …

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