Towards sector-based attribution using intra-city variations in satellite-based emission ratios between CO<sub>2</sub> and CO
<p>Carbon dioxide (CO<span class="inline-formula"><sub>2</sub></span>) and air pollutants such as carbon monoxide (CO) are co-emitted by many combustion sources. Previous efforts have combined satellite-based observations of multiple tracers to calculate their...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2022-11-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://acp.copernicus.org/articles/22/14547/2022/acp-22-14547-2022.pdf |
| Summary: | <p>Carbon dioxide (CO<span class="inline-formula"><sub>2</sub></span>) and air pollutants such as carbon monoxide (CO) are co-emitted by many combustion sources. Previous efforts have combined satellite-based observations of multiple tracers to calculate their emission ratio (ER) for inferring combustion efficiency at the regional to city scale. Very few studies have focused on combustion efficiency at the sub-city scale or related it to emission sectors using space-based observations. Several factors are important for interpreting and deriving spatially resolved ERs from asynchronous satellite measurements, including (1) variations in meteorological conditions given the mismatch in satellite overpass times, (2) differences in vertical sensitivity of the retrievals (i.e., averaging kernel profiles), (3) interferences from the biosphere and biomass burning, and (4) the mismatch in the daytime variations of CO and CO<span class="inline-formula"><sub>2</sub></span> emissions. In this study, we extended an established emission estimate approach to arrive at spatially resolved ERs based on retrieved column-averaged CO<span class="inline-formula"><sub>2</sub></span> (XCO<span class="inline-formula"><sub>2</sub></span>) from the Snapshot Area Mapping (SAM) mode of the Orbiting Carbon Observatory-3 (OCO-3) and column-averaged CO from the TROPOspheric Monitoring Instrument (TROPOMI).</p>
<p>To evaluate the influences of the confounding factors listed above and further attribute intra-urban variations in ERs to certain sectors, we leveraged a Lagrangian atmospheric transport model with an urban land cover classification dataset and reported ER<span class="inline-formula"><sub>CO</sub></span> values from the sounding level to the overpass and city level. We found that the differences in overpass times and averaging kernels between OCO and TROPOMI strongly affect the estimated spatially resolved ER<span class="inline-formula"><sub>CO</sub></span>. Specifically, a time difference of <span class="inline-formula">>3</span> h typically led to dramatic changes in wind directions and urban plume shapes, thereby making the calculation of accurate sounding-specific ER<span class="inline-formula"><sub>CO</sub></span> difficult. After removing such cases from consideration and applying a simple plume shift method when necessary to account for changes in wind direction and speed, we discovered significant contrasts in combustion efficiencies between (1) two megacities versus two industry-oriented cities and (2) different regions within a city, based on six nearly coincident overpasses per city. Results suggest that the ER<span class="inline-formula"><sub>CO</sub></span> impacted by heavy industry in Los Angeles is slightly lower than the overall city-wide value (<span class="inline-formula"><10</span> ppb-CO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M12" display="inline" overflow="scroll" dspmath="mathml"><mo>/</mo></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="8pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="6bfc4ae3491d603d986b6e1d0e6866cf"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-22-14547-2022-ie00001.svg" width="8pt" height="14pt" src="acp-22-14547-2022-ie00001.png"/></svg:svg></span></span>ppm-CO<span class="inline-formula"><sub>2</sub></span>). In contrast, the ER<span class="inline-formula"><sub>CO</sub></span> related to heavy industry in Shanghai is much higher than Shanghai's city mean and more aligned with the city means of two selected industry-oriented cities in China (approaching 20 ppb-CO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M15" display="inline" overflow="scroll" dspmath="mathml"><mo>/</mo></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="8pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="7572a9d7afeaa92ba0e8bb6f686362bd"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-22-14547-2022-ie00002.svg" width="8pt" height="14pt" src="acp-22-14547-2022-ie00002.png"/></svg:svg></span></span>ppm-CO<span class="inline-formula"><sub>2</sub></span>). Although investigations based on a larger number of satellite overpasses are needed, our unique approach (i.e., without using sector-specific information from emission inventories) provides new insights into assessing combustion efficiency within a city from future satellite missions, such as those that will map column CO<span class="inline-formula"><sub>2</sub></span> and CO concentrations simultaneously with high spatiotemporal resolutions.</p> |
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| ISSN: | 1680-7316 1680-7324 |