Abstract
The COVID-19 pandemic is the single largest event in contemporary history in terms of the global restriction of mobility, with the majority of the world population experiencing various forms of “lockdown”. This phenomenon incurred increased amounts of teleworking and time spent at home, fewer trips to shops, closure of retail outlets selling non-essential goods, and the near disappearance of leisure and recreational activities. This paper presents a novel method for an economy-wide estimate of the emissions reductions caused by the restriction of movement. Using a global multiregional macro-economic model complemented by Google Community Mobility Reports (CMRs) and national transport data, we cover 129 individual countries and quantify direct and indirect global emissions reductions of greenhouse gases (GHG; 1173 Mt), PM2.5 (0.23 Mt), SO2 (1.57 Mt), and NOx (3.69 Mt). A statistically significant correlation is observed between cross-country emission reductions and the stringency of mobility restriction policies. Due to the aggregated nature of the CMRs, we develop different scenarios linked to consumption, work, and lifestyle aspects. Global reductions are on the order of 1–3% (GHG), 1–2% (PM2.5), 0.5–2.8% (SO2), and 3–4% (NOx). Our results can help support crucial decision making in the post-COVID world, with quantified information about how direct and indirect consequences of mobility changes benefit the environment.
Highlights
The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2),[1] has brought the world to a standstill
At least 93% of the world population resides in countries with restrictions in place, and more than 3 billion people are under permanent border closures.[4,5]
A tool developed by the University of Oxford (OxCGRT) measures the “stringency” of policies across a range of indicators referring to containment and closure, calculated in the form of a “stringency index”
Summary
The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2),[1] has brought the world to a standstill. Existing emissions reduction estimates do exist but either cover single countries (e.g., China[15] or Italy16) and cities[17] or rely on simplified modeling and do not take into account economy-wide global implications.[18] unlike other ongoing work[19] based on Google CMRs which does not use input−output analysis, utilizes European averages to represent multiple countries, and assumes Google data to represent full traffic volume reductions we utilize primary data on modal transport shares and car shares for 129 individual countries and develop a range of scenarios with aspects linked to consumption, work, and lifestyle choices to account for the inherent uncertainty caused by the aggregated nature of CMRs. The following section describes the data and methods we used, and it is followed by key results and their discussion.
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