European primary emissions of criteria pollutants and greenhouse gases in 2020 modulated by the COVID-19 pandemic disruptions
<p>We present a European dataset of daily sector-, pollutant- and country-dependent emission adjustment factors associated with the COVID-19 mobility restrictions for the year 2020. We considered metrics traditionally used to estimate emissions, such as energy statistics or traffic counts, as...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2022-06-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/14/2521/2022/essd-14-2521-2022.pdf |
| Summary: | <p>We present a European dataset of daily sector-,
pollutant- and country-dependent emission adjustment factors associated with
the COVID-19 mobility restrictions for the year 2020. We considered metrics
traditionally used to estimate emissions, such as energy statistics or
traffic counts, as well as information derived from new mobility indicators
and machine learning techniques. The resulting dataset covers a total of
nine emission sectors, including road transport, the energy industry, the
manufacturing industry, residential and commercial combustion, aviation,
shipping, off-road transport, use of solvents, and fugitive emissions from
transportation and distribution of fossil fuels. The dataset was produced to
be combined with the Copernicus CAMS-REG_v5.1 2020
business-as-usual (BAU) inventory, which provides high-resolution (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">0.1</mn><msup><mi/><mo>∘</mo></msup><mo>×</mo><mn mathvariant="normal">0.05</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="58pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="69623878d96e7494fea8765a91ebdb95"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="essd-14-2521-2022-ie00001.svg" width="58pt" height="11pt" src="essd-14-2521-2022-ie00001.png"/></svg:svg></span></span>) emission estimates for 2020 omitting the impact of the COVID-19
restrictions. The combination of both datasets allows quantifying spatially
and temporally resolved reductions in primary emissions from both criteria
pollutants (<span class="inline-formula">NO<sub><i>x</i></sub></span>, <span class="inline-formula">SO<sub>2</sub></span>, non-methane volatile organic compounds – NMVOCs, <span class="inline-formula">NH<sub>3</sub></span>, CO, PM<span class="inline-formula"><sub>10</sub></span> and
PM<span class="inline-formula"><sub>2.5</sub></span>) and greenhouse gases (<span class="inline-formula">CO<sub>2</sub></span> fossil fuel, <span class="inline-formula">CO<sub>2</sub></span> biofuel and
<span class="inline-formula">CH<sub>4</sub></span>), as well as assessing the contribution of each emission sector and
European country to the overall emission changes. Estimated overall emission
changes in 2020 relative to BAU emissions were as follows: <span class="inline-formula">−</span>10.5 % for
<span class="inline-formula">NO<sub><i>x</i></sub></span> (<span class="inline-formula">−</span>602 kt), <span class="inline-formula">−</span>7.8 % (<span class="inline-formula">−</span>260.2 Mt) for <span class="inline-formula">CO<sub>2</sub></span> from fossil fuels,
<span class="inline-formula">−</span>4.7 % (<span class="inline-formula">−</span>808.5 kt) for CO, <span class="inline-formula">−</span>4.6 % (<span class="inline-formula">−</span>80 kt) for <span class="inline-formula">SO<sub>2</sub></span>, <span class="inline-formula">−</span>3.3 % (<span class="inline-formula">−</span>19.1 Mt) for <span class="inline-formula">CO<sub>2</sub></span> from biofuels, <span class="inline-formula">−</span>3.0 % (<span class="inline-formula">−</span>56.3 kt) for PM<span class="inline-formula"><sub>10</sub></span>, <span class="inline-formula">−</span>2.5 %
(<span class="inline-formula">−</span>173.3 kt) for NMVOCs, <span class="inline-formula">−</span>2.1 % (<span class="inline-formula">−</span>24.3 kt) for PM<span class="inline-formula"><sub>2.5</sub></span>, <span class="inline-formula">−</span>0.9 % (<span class="inline-formula">−</span>156.1 kt) for <span class="inline-formula">CH<sub>4</sub></span> and <span class="inline-formula">−</span>0.2 % (<span class="inline-formula">−</span>8.6 kt) for <span class="inline-formula">NH<sub>3</sub></span>. The most pronounced
drop in emissions occurred in April (up to <span class="inline-formula">−</span>32.8 % on average for
<span class="inline-formula">NO<sub><i>x</i></sub></span>) when mobility restrictions were at their maxima. The emission
reductions during the second epidemic wave between October and December
were 3 to 4 times lower than those occurred during the spring
lockdown, as mobility restrictions were generally softer (e.g. curfews,
limited social gatherings). Italy, France, Spain, the United Kingdom and
Germany were, together, the largest contributors to the total EU27 + UK (27 member states of the European Union and the UK)
absolute emission decreases. At the sectoral level, the largest emission
declines were found for aviation (<span class="inline-formula">−</span>51 % to <span class="inline-formula">−</span>56 %), followed by road
transport (<span class="inline-formula">−</span>15.5 % to <span class="inline-formula">−</span>18.8 %), the latter being the main driver of the
estimated reductions for the majority of pollutants. The collection of
COVID-19 emission adjustment factors (<a href="https://doi.org/10.24380/k966-3957">https://doi.org/10.24380/k966-3957</a>,
Guevara et al., 2022) and the CAMS-REG_v5.1 2020 BAU gridded
inventory (<a href="https://doi.org/10.24380/eptm-kn40">https://doi.org/10.24380/eptm-kn40</a>, Kuenen et al., 2022b) have
been produced in support of air quality modelling studies.</p> |
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| ISSN: | 1866-3508 1866-3516 |