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The impact of emissions of volatile organic compounds (VOCs) to the atmosphere on the production of secondary pollutants, such as ozone and secondary organic aerosol (SOA), is mediated by the concentration of nitric oxide (NO). Polluted urban atmospheres are typically considered to be "high-NO"environments, while remote regions such as rainforests, with minimal anthropogenic influences, are considered to be "low NO". However, our observations from central Beijing show that this simplistic separation of regimes is flawed. Despite being in one of the largest megacities in the world, we observe formation of gas- and aerosol-phase oxidation products usually associated with low-NO "rainforest-like"atmospheric oxidation pathways during the afternoon, caused by extreme suppression of NO concentrations at this time. Box model calculations suggest that during the morning high-NO chemistry predominates (95 %) but in the afternoon low-NO chemistry plays a greater role (30 %). Current emissions inventories are applied in the GEOS-Chem model which shows that such models, when run at the regional scale, fail to accurately predict such an extreme diurnal cycle in the NO concentration. With increasing global emphasis on reducing air pollution, it is crucial for the modelling tools used to develop urban air quality policy to be able to accurately represent such extreme diurnal variations in NO to accurately predict the formation of pollutants such as SOA and ozone.

The impact of emissions of volatile organic compounds (VOCs) to the atmosphere on the production of secondary pollutants, such as ozone and secondary organic aerosol (SOA), is mediated by the concentration of nitric oxide (NO). Polluted urban atmospheres are typically considered to be "high-NO"environments, while remote regions such as rainforests, with minimal anthropogenic influences, are considered to be "low NO". However, our observations from central Beijing show that this simplistic separation of regimes is flawed. Despite being in one of the largest megacities in the world, we observe formation of gas- and aerosol-phase oxidation products usually associated with low-NO "rainforest-like"atmospheric oxidation pathways during the afternoon, caused by extreme suppression of NO concentrations at this time. Box model calculations suggest that during the morning high-NO chemistry predominates (95 %) but in the afternoon low-NO chemistry plays a greater role (30 %). Current emissions inventories are applied in the GEOS-Chem model which shows that such models, when run at the regional scale, fail to accurately predict such an extreme diurnal cycle in the NO concentration. With increasing global emphasis on reducing air pollution, it is crucial for the modelling tools used to develop urban air quality policy to be able to accurately represent such extreme diurnal variations in NO to accurately predict the formation of pollutants such as SOA and ozone.

The impact of emissions of volatile organic compounds (VOCs) to the atmosphere on the production of secondary pollutants, such as ozone and secondary organic aerosol (SOA), is mediated by the concentration of nitric oxide (NO). Polluted urban atmospheres are typically considered to be “high-NO” environments, while remote regions such as rainforests, with minimal anthropogenic influences, are considered to be “low NO”. However, our observations from central Beijing show that this simplistic separation of regimes is flawed. Despite being in one of the largest megacities in the world, we observe formation of gas- and aerosol-phase oxidation products usually associated with low-NO “rainforest-like” atmospheric oxidation pathways during the afternoon, caused by extreme suppression of NO concentrations at this time. Box model calculations suggest that during the morning high-NO chemistry predominates (95 %) but in the afternoon low-NO chemistry plays a greater role (30 %). Current emissions inventories are applied in the GEOS-Chem model which shows that such models, when run at the regional scale, fail to accurately predict such an extreme diurnal cycle in the NO concentration. With increasing global emphasis on reducing air pollution, it is crucial for the modelling tools used to develop urban air quality policy to be able to accurately represent such extreme diurnal variations in NO to accurately predict the formation of pollutants such as SOA and ozone.

The impact of emissions of volatile organic compounds (VOCs) to the atmosphere on the production of secondary pollutants, such as ozone and secondary organic aerosol (SOA), is mediated by the concentration of nitric oxide (NO). Polluted urban atmospheres are typically considered to be "high-NO"environments, while remote regions such as rainforests, with minimal anthropogenic influences, are considered to be "low NO". However, our observations from central Beijing show that this simplistic separation of regimes is flawed. Despite being in one of the largest megacities in the world, we observe formation of gas- and aerosol-phase oxidation products usually associated with low-NO "rainforest-like"atmospheric oxidation pathways during the afternoon, caused by extreme suppression of NO concentrations at this time. Box model calculations suggest that during the morning high-NO chemistry predominates (95 %) but in the afternoon low-NO chemistry plays a greater role (30 %). Current emissions inventories are applied in the GEOS-Chem model which shows that such models, when run at the regional scale, fail to accurately predict such an extreme diurnal cycle in the NO concentration. With increasing global emphasis on reducing air pollution, it is crucial for the modelling tools used to develop urban air quality policy to be able to accurately represent such extreme diurnal variations in NO to accurately predict the formation of pollutants such as SOA and ozone.

The impact of emissions of volatile organic compounds (VOCs) to the atmosphere on the production of secondary pollutants, such as ozone and secondary organic aerosol (SOA), is mediated by the concentration of nitric oxide (NO). Polluted urban atmospheres are typically considered to be "high-NO"environments, while remote regions such as rainforests, with minimal anthropogenic influences, are considered to be "low NO". However, our observations from central Beijing show that this simplistic separation of regimes is flawed. Despite being in one of the largest megacities in the world, we observe formation of gas- and aerosol-phase oxidation products usually associated with low-NO "rainforest-like"atmospheric oxidation pathways during the afternoon, caused by extreme suppression of NO concentrations at this time. Box model calculations suggest that during the morning high-NO chemistry predominates (95 %) but in the afternoon low-NO chemistry plays a greater role (30 %). Current emissions inventories are applied in the GEOS-Chem model which shows that such models, when run at the regional scale, fail to accurately predict such an extreme diurnal cycle in the NO concentration. With increasing global emphasis on reducing air pollution, it is crucial for the modelling tools used to develop urban air quality policy to be able to accurately represent such extreme diurnal variations in NO to accurately predict the formation of pollutants such as SOA and ozone.

The impact of emissions of volatile organic compounds (VOCs) to the atmosphere on the production of secondary pollutants, such as ozone and secondary organic aerosol (SOA), is mediated by the concentration of nitric oxide (NO). Polluted urban atmospheres are typically considered to be “high-NO” environments, while remote regions such as rainforests, with minimal anthropogenic influences, are considered to be “low NO”. However, our observations from central Beijing show that this simplistic separation of regimes is flawed. Despite being in one of the largest megacities in the world, we observe formation of gas- and aerosol-phase oxidation products usually associated with low-NO “rainforest-like” atmospheric oxidation pathways during the afternoon, caused by extreme suppression of NO concentrations at this time. Box model calculations suggest that during the morning high-NO chemistry predominates (95 %) but in the afternoon low-NO chemistry plays a greater role (30 %). Current emissions inventories are applied in the GEOS-Chem model which shows that such models, when run at the regional scale, fail to accurately predict such an extreme diurnal cycle in the NO concentration. With increasing global emphasis on reducing air pollution, it is crucial for the modelling tools used to develop urban air quality policy to be able to accurately represent such extreme diurnal variations in NO to accurately predict the formation of pollutants such as SOA and ozone.

China’s air quality problems are well publicised; in 2010, 1.2 million premature deaths were attributed to outdoor air pollution in China. One of the major air quality issues is high concentrations of nitrogen oxides (NOx). China is the largest NOx emitter, contributing an estimated 18 % to global NOx emissions. Beijing itself is reported to have NO2 concentrations 42 % higher than the annual national standard. Given the high levels of pollution, increased focus has been placed on improving emissions estimates which are typically developed using a ‘bottom-up’ approach where emissions are predicted from their sources. Emission inventories in China have large uncertainties and are rapidly changing with time in response to economic development, environmental regulation and new technologies. In fact, China is the largest contributor to the uncertainty in the source and the magnitude of air pollutants in air quality models. Recent studies have shown a discrepancy between NOx inventories and measured NOx emissions for UK cities, highlighting the limitations of bottom-up emissions inventories and the importance of accurate measurement data to improve the estimates. 5 Hz measurements of NOx and CO concentration were made as part of the Air Pollutants in Beijing (AIRPOLL-Beijing) project during two field campaigns in Nov-Dec 2016 and May-June 2017. Sampling took place from an inlet co-located with a sonic anemometer at 102 m on a meteorological tower in central Beijing. Analysis of the covariance between vertical wind speed and concentration enabled the calculation of emission flux, with an estimated footprint of between 2 – 5 km from the tower (which typically included some major ring roads and expressways). Fluxes were quantified using the continuous wavelet transformation (CWT) method, which enabled one minute resolved fluxes to be calculated. These data were compared to existing emissions estimates from the Multi-resolution Emission Inventory for China (MEIC). It is anti

China’s air quality problems are well publicised; in 2010, 1.2 million premature deaths were attributed to outdoor air pollution in China. One of the major air quality issues is high concentrations of nitrogen oxides (NOx). China is the largest NOx emitter, contributing an estimated 18 % to global NOx emissions. Beijing itself is reported to have NO2 concentrations 42 % higher than the annual national standard. Given the high levels of pollution, increased focus has been placed on improving emissions estimates which are typically developed using a ‘bottom-up’ approach where emissions are predicted from their sources. Emission inventories in China have large uncertainties and are rapidly changing with time in response to economic development, environmental regulation and new technologies. In fact, China is the largest contributor to the uncertainty in the source and the magnitude of air pollutants in air quality models. Recent studies have shown a discrepancy between NOx inventories and measured NOx emissions for UK cities, highlighting the limitations of bottom-up emissions inventories and the importance of accurate measurement data to improve the estimates. 5 Hz measurements of NOx and CO concentration were made as part of the Air Pollutants in Beijing (AIRPOLL-Beijing) project during two field campaigns in Nov-Dec 2016 and May-June 2017. Sampling took place from an inlet co-located with a sonic anemometer at 102 m on a meteorological tower in central Beijing. Analysis of the covariance between vertical wind speed and concentration enabled the calculation of emission flux, with an estimated footprint of between 2 – 5 km from the tower (which typically included some major ring roads and expressways). Fluxes were quantified using the continuous wavelet transformation (CWT) method, which enabled one minute resolved fluxes to be calculated. These data were compared to existing emissions estimates from the Multi-resolution Emission Inventory for China (MEIC). It is anti