Evaluation of nitrogen oxides (NO<sub><i>x</i></sub>) sources and sinks and ozone production in Colombia and surrounding areas
<p>In Colombia, industrialization and a shift towards intensified agriculture have led to increased emissions of air pollutants. However, the baseline state of air quality in Colombia is relatively unknown. In this study we aim to assess the baseline state of air quality in Colombia with a foc...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2020-08-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://acp.copernicus.org/articles/20/9441/2020/acp-20-9441-2020.pdf |
| Summary: | <p>In Colombia, industrialization and a shift towards intensified agriculture have led to increased emissions of air pollutants. However, the baseline state of air quality in Colombia is relatively unknown. In this study we aim to assess the baseline state of air quality in Colombia with a focus on the spatial and temporal variability in emissions and atmospheric burden of nitrogen oxides (<span class="inline-formula">NO<sub><i>x</i></sub></span> = NO + <span class="inline-formula">NO<sub>2</sub></span>) and evaluate surface <span class="inline-formula">NO<sub><i>x</i></sub></span>, ozone (<span class="inline-formula">O<sub>3</sub></span>) and carbon monoxide (CO) mixing ratios. We quantify the magnitude and spatial distribution of the four major <span class="inline-formula">NO<sub><i>x</i></sub></span> sources (lightning, anthropogenic activities, soil biogenic emissions and biomass burning) by integrating global <span class="inline-formula">NO<sub><i>x</i></sub></span> emission inventories into the mesoscale meteorology and atmospheric chemistry model, namely Weather Research and Forecasting (WRF) coupled with Chemistry (collectively WRF-Chem), at a similar resolution (<span class="inline-formula">∼25</span> km) to the Emission Database for Global Atmospheric Research (EDGAR) anthropogenic emission inventory and the Ozone Monitoring Instrument (OMI) remote sensing observations. The model indicates the largest contribution by lightning emissions (1258 Gg N yr<span class="inline-formula"><sup>−1</sup></span>), even after already significantly reducing the emissions, followed by anthropogenic (933 Gg N yr<span class="inline-formula"><sup>−1</sup></span>), soil biogenic (187 Gg N yr<span class="inline-formula"><sup>−1</sup></span>) and biomass burning emissions (104 Gg N yr<span class="inline-formula"><sup>−1</sup></span>). The comparison with OMI remote sensing observations indicated a mean bias of tropospheric <span class="inline-formula">NO<sub>2</sub></span> columns over the whole domain (WRF-Chem minus OMI) of 0.02 (90 % CI: [<span class="inline-formula">−0.43</span>, 0.70]) <span class="inline-formula">×10<sup>15</sup></span> molecules cm<span class="inline-formula"><sup>−2</sup></span>, which is <span class="inline-formula"><5</span> % of the mean column. However, the simulated <span class="inline-formula">NO<sub>2</sub></span> columns are overestimated and underestimated in regions where lightning and biomass burning emissions dominate, respectively. WRF-Chem was unable to capture <span class="inline-formula">NO<sub><i>x</i></sub></span> and CO urban pollutant mixing ratios, neither in timing nor in magnitude. Yet, WRF-Chem was able to simulate the urban diurnal cycle of <span class="inline-formula">O<sub>3</sub></span> satisfactorily but with a systematic overestimation of 10 parts per billion (ppb) due to the equally large underestimation of <span class="inline-formula">NO</span> mixing ratios and, consequently, titration. This indicates that these city environments are in the <span class="inline-formula">NO<sub><i>x</i></sub></span>-saturated regime with frequent <span class="inline-formula">O<sub>3</sub></span> titration. We conducted sensitivity experiments with an online meteorology–chemistry single-column model (SCM) to evaluate how WRF-Chem subgrid-scale-enhanced emissions could explain an improved representation of the observed <span class="inline-formula">O<sub>3</sub></span>, CO and <span class="inline-formula">NO<sub><i>x</i></sub></span> diurnal cycles. Interestingly, the SCM simulation, showing especially a shallower nocturnal inversion layer, results in a better representation of the observed diurnal cycle of urban pollutant mixing ratios without an enhancement in emissions. This stresses that, besides application of higher-resolution emission inventories and model experiments, the diurnal cycle in boundary layer dynamics (and advection) should be critically evaluated in models such as WRF-Chem to assess urban air quality. Overall, we present a concise method to quantify air quality in regions with limited surface measurements by integrating in situ and remote sensing observations. This study identifies four distinctly different source regions and shows their interannual and seasonal variability during the last 1.5 decades. It serves as a base to assess scenarios of future air quality in Colombia or similar regions with contrasting emission regimes, complex terrain and a limited air quality monitoring network.</p> |
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| ISSN: | 1680-7316 1680-7324 |