THE ECONOMICS OF SPACE: Warehouse Development and Environmental Justice in the Consumer Society

IVAN MELCHOR

Ivan Melchor is a research assistant with the VizE Lab for Ethnographic Data Visualization at Princeton University. His research focuses on public policy and environmental justice, using ethnographic and quantitative methods.

ABSTRACT

Warehouse development has exploded in the past 20 years in the United States. This phenomenon has been driven by the shift to online consumption, a shift further exacerbated in the wake of the COVID-19 pandemic. Research has shown that warehouses produce negative externalities such as air and noise pollution and environmental degradation. This article explores warehouse development in New Jersey as a microcosm of the country, using both dasymetric mapping and a race prediction algorithm to show how racial and economic disparities worsen the closer one lives to a warehouse. This article explores the conditions under which the spatiality of racism continues to be re-created, calling into question policy reforms that claim to address warehouse pollution before analyzing the limitations of environmental justice and the right to space in the ‘consumer society.’

Warehouse development has exploded in the past 20 years in the United States. This phenomenon has been driven by the shift to online consumption, a shift further exacerbated in the wake of the COVID-19 pandemic. Research has shown that warehouses produce negative externalities such as air and noise pollution and environmental degradation. This article explores warehouse development in New Jersey as a microcosm of the country, using both dasymetric mapping and a race prediction algorithm to show how racial and economic disparities worsen the closer one lives to a warehouse. This article explores the conditions under which the spatiality of racism continues to be re-created, calling into question policy reforms that claim to address warehouse pollution before analyzing the limitations of environmental justice and the right to space in the ‘consumer society.’

INTRODUCTION

In the United States, warehouse development has been a profitable venture for state and private actors for decades but has spiked in recent years. New Jersey has become a popular site for development due to its proximity to major markets and port and highway systems. It is estimated that there are 1,900 warehouses in the state, a 36% increase since 2000 (Moffatt 2023). Policy experts attribute this phenomenon to land-use incentives. Local governments rely on property taxes to fund local services such as schools, but residential properties often generate more costs than revenue, whereas industrial and commercial properties raise revenue and cost comparatively less. This has led to a preference for non-residential wealth generators, i.e. warehouses, who benefit from this recursive loop. The legal system has also enabled warehouse developers; once they submit applications for warehouse sites on land designated for industrial use, there is little that municipalities can do to stop construction without risking litigation.

METHODOLOGY

To perform this analysis, I used a dasymetric model to account for land use coverage and population distribution. Dasymetric mapping is a geospatial technique that uses information such as land cover types to distribute data more accurately to selected boundaries like census tracts (EPA 2023). To disaggregate the population, I created a dataset of investigatory variables measuring population, race, voter eligibility, age, and population below the poverty level, ranging from 50% to 500% based on American Community Survey (ACS) 5-year estimates from 2016 to 2020 at the census tract level. I obtained impervious coverage and land use/land cover data from 2015 from the NJ Department of Environmental Protection and cross-matched both datasets to identify all residential buildings in New Jersey. I applied weights according to building type (rural single unit, low density, medium density, high density) to control for variance in building density among rural and urban areas. I then distributed the ACS population dataset and ran an analysis in ArcGIS, identifying 2,547,827 residential buildings. Using a sample dataset of 517 warehouses obtained from a Simple Analytics database, I estimated a sample population of those residing within 1 mile, 0.5 miles, and 0.25 miles of a warehouse.

To supplement the dasymetric model, I analyzed the spatial distribution of individuals in addition to neighborhoods. Voter records allow one to examine the distribution of registered voters across the state and map out their proximity to warehouse sitings as a proxy for the total population. I filed an Open Public Records Act (OPRA) request with the NJ Department of Elections to obtain a dataset of 6.44 million voters containing first and last names, residential addresses, ages, and party registration. Voter gender and race are not recorded in voter list records. To predict the race of voters, I used a fully Bayesian Race Predictor Algorithm (fBISG) that uses an individual’s first and last name, county of residence, and party registration to impute demographic characteristics using the wru package in R (Imai et al 2022).

A probability score was assigned to each individual in five categories: White, Black, Hispanic, Asian, and Other. Each voter’s residential address was then geocoded in ArcGIS. Rather than assign race to individual voters, I summed the mean probability of each race category for the total voter population and compared it to that of voters residing within 1 mile, 0.5 miles, and 0.25 miles of a warehouse.

RESULTS

The dasymetric model confirms the hypothesis that racial and economic inequality increases the closer one resides to a warehouse. Table 1 shows the model results, comparing the statewide population to our sample populations at different distances. Racial disparity increases at each marker for Black and Latino populations. The Black population makes up 13% of the state population, but 21% of residents within 0.25 miles of a warehouse.

The share of the White population decreases from 66% at the state level to 48% within 0.25 miles of a warehouse. The Latino population makes up 20% of the state population, but 37% of residents within 0.25 miles of a warehouse, the largest spike of any measured group. Using the sample population, it is estimated that approximately 52% of all Hispanic/Latino residents in New Jersey reside within one mile of a warehouse.

Regarding poverty level indicators, the greatest jump in disproportionality is observed for those living below 150%, 200%, and 300% of the federal poverty level. As these measures increase in percentage, overrepresentation also increases before holding steady at 400% and 500% below the federal poverty level. The model shows that, regarding class, warehouse siting is not a phenomenon that afflicts the poor exclusively (Yuan, 2021); rather, it is actively sited away from the wealthy.

The fBISG model reaffirms the findings of the dasymetric model. Using the NJ voter list, an estimated 1,061,787 registered voters reside within 1 mile of our warehouse sample population. The mean probability of being White drops from 0.61 to 0.36 within 0.25 miles of a warehouse. The probability of being Black or Hispanic rises to 0.16 and 0.35, respectively. The findings are shown below in Table 2.

POLICY INTERVENTIONS

In 2020, New Jersey passed the Environmental Justice Law, mandating that the NJ Department of Environmental Protection (NJDEP) reject applications for facilities that pose an environmental risk if they disproportionately impact “over-burdened communities” (Redd, 2020). These facilities included incinerators, power plants, sewage treatment plants, landfills, and major sources of air pollution as defined by the federal Clean Air Act. The state defined an over-burdened community as any census block in which 35% of households qualified as low income; 40% of residents identified as a minority; or at least 40% had limited English proficiency (N.J.S.A 12:1D-158).

In 2022, the NJ Office of Planning Advocacy published a report confirming that warehouses did not fall under the jurisdiction of the Environmental Justice Law because they were not a direct source of air pollution (NJSPC 2022).

Instead, the NJDEP adopted the Advanced Clean Trucks Rule (ACT). The ACT rule requires that manufacturers sell and deliver pollution-free zero-emission trucks to New Jersey beginning in 2025 and requires 40-75 percent new zero-emission truck sales by 2035. In addition, the NJDEP adopted the Omnibus rules, mandating a 75 percent reduction in nitrogen oxide (NOx) emissions from the engines in new gasoline and diesel trucks sold between 2025 and 2026 and a 90 percent reduction for trucks sold beginning in 2027 in the state. (Environment America 2023).

The Advanced Clean Trucks and Omnibus Rules were designed to address the ‘burden’ of diesel trucks on residents via supply-side interventions. Notably, however, these rules did not mandate that warehouses use zero-emission vehicles nor adopt a timeline for their onboarding (Miles 2021). Rather than evidence of the technocratic state’s ability to address social problems “within the confines of capitalism” (Mattick 1972), the NJDEP rules revealed an intent to bring warehouse development “into the future” and preserve the network of economic actors dependent on its proliferation. Thus, the state’s warehouse policy signaled an inflection point, not in how the state governed ‘burdened’ communities but in how it sustained growth. That today, warehouses are zoned for industrial land use by municipalities is symbolic that an internal substitution has taken place in a system that remains “in all essentials unchanged” (Baudrillard 1998).

New Jersey’s legal tradition as a “home rule” state means that municipalities dictate land-use decisions, limiting the state’s authority over zoning. In view of this, planners and policymakers continue to advocate for technology-based policy solutions such as the electrification of trucks, the vertical scaling of warehouses, and the installation of rooftop solar panels. Such techno-managerial policy solutions promise a ‘green future.’ Still, without a redistributive justice mechanism for communities presently impacted by environmental injustice, they serve only as a “technological veil that conceals the reproduction of inequality and enslavement” (Marcuse 1964). Proposals for regionalization of land use decisions hold promise due to their ability to involve more municipalities in the siting process. But without a reparative dimension, such policy proposals will only mask the racist and classist zoning laws that segregate the communities presently afflicted, making it appear as if “time has vanished from space” (Lefebvre 1974).

ENVIRONMENTAL JUSTICE AND THE RIGHT TO SPACE

As marginalized communities experience alienation from the state, there has been a renewed appeal for a ‘right to space’ that, like the ‘right to clean air,’ originates from a deontological (rights-based) environmental justice paradigm and aspires to reform via the recognition of the individual’s rights. Henri Lefebvre defines space as “more than just a container; rather, space is social morphology; it is to lived experience what form itself is to the living organism” (Lefebvre 1974). According to Lefebvre, society has been colonized by abstract space, which “facilitates capitalist production, distribution, and consumption, but that is itself transformed into a commodity, pulverized and sold off in parcels” (Stanek 2011).

If, in fact, space has been commodified and “there is no right to space until there no longer is space for everyone” (Baudrillard 1998), then one is left with a different question altogether. Rather than framing the ‘right to space’ as that which might yet arrive, is it possible it has arrived too late? An inversion is required, from using the individual as the locus of consumerism and reform towards the social production of space that preconditions consumption and environmental injustice. Such an inversion would denaturalize the warehouse as a societal ‘fact.’ Thereby revealing it as purely “our own creation; alienated labor—dead labor—set in motion” (Thompson and Nishat-Botero 2023) far removed from the production of social well-being.

CONCLUSION

Although this paper focuses on warehouse development in New Jersey, the methods applied can be used to investigate the demographic makeup of communities impacted by environmental injustice elsewhere. This paper sheds light on how commonplace racial and economic disparities have become in warehouse “sacrifice zones” while also illustrating how New Jersey planning and public policy initiatives have failed to address uneven siting patterns. The rising popularity of “smart” and “green” growth initiatives has revealed an appetite for continued growth and investment in the logistics economic sector. Still, it has yet to address the alarming rates at which warehouses are sited in low-income communities that are unable to contest their arrival. In the case of warehouse development, environmental justice movements have been subjugated by “smart” and “green” growth policies that “promote new forms of inequality, marginality, exclusion, and environmental hazard” (Kaika et al., 2023). If environmental justice is to become a social transformer, then planning must challenge the presupposition of economic growth as a function of the city.

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