The COVID-19 lockdowns led to major reductions in air pollutant emissions. Here, we quantitatively evaluate changes in ambient NO2, O3, and PM2.5 concentrations arising from these emission changes in 11 cities globally by applying a deweathering machine learning technique. Sudden decreases in deweathered NO2 concentrations and increases in O3 were observed in almost all cities. However, the decline in NO2 concentrations attributable to the lockdowns was not as large as expected, at reductions of 10 to 50%. Accordingly, O3 increased by 2 to 30% (except for London), the total gaseous oxidant (Ox = NO2 + O3) showed limited change, and PM2.5 concentrations decreased in most cities studied but increased in London and Paris. Our results demonstrate the need for a sophisticated analysis to quantify air quality impacts of interventions and indicate that true air quality improvements were notably more limited than some earlier reports or observational data suggested.
Abstract. A 5-year Clean Air Action Plan was implemented in 2013 to reduce air
pollutant emissions and improve ambient air quality in Beijing. Assessment
of this action plan is an essential part of the decision-making process to
review its efficacy and to develop new policies. Both
statistical and chemical transport modelling have been previously applied to
assess the efficacy of this action plan. However, inherent uncertainties in
these methods mean that new and independent methods are required to support
the assessment process. Here, we applied a machine-learning-based random
forest technique to quantify the effectiveness of Beijing's action plan by
decoupling the impact of meteorology on ambient air quality. Our results
demonstrate that meteorological conditions have an important impact on the
year-to-year variations in ambient air quality. Further analyses show that
the PM2.5 mass concentration would have broken the target of the plan
(2017 annual PM2.5<60 µg m−3) were it not for the
meteorological conditions in winter 2017 favouring the dispersion of air
pollutants. However, over the whole period (2013–2017), the primary
emission controls required by the action plan have led to significant
reductions in PM2.5, PM10, NO2, SO2, and CO from 2013 to 2017 of approximately 34 %, 24 %, 17 %, 68 %, and 33 %, respectively, after meteorological correction. The marked decrease in PM2.5 and SO2 is largely attributable to a reduction in coal
combustion. Our results indicate that the action plan has been highly
effective in reducing the primary pollution emissions and improving air
quality in Beijing. The action plan offers a successful example for
developing air quality policies in other regions of China and other
developing countries.
Abstract. Primary productivity of continental and marine ecosystems is often limited or co-limited by phosphorus. Deposition of atmospheric aerosols provides the major external source of phosphorus to marine surface waters. However, only a fraction of deposited aerosol phosphorus is water soluble and available for uptake by phytoplankton. We propose that atmospheric acidification of aerosols is a prime mechanism producing soluble phosphorus from soil-derived minerals. Acid mobilization is expected to be pronounced where polluted and dust-laden air masses mix. Our hypothesis is supported by the soluble compositions and reconstructed pH values for atmospheric particulate matter samples collected over a 5-yr period at Finokalia, Crete. In addition, at least tenfold increase in soluble phosphorus was observed when Saharan soil and dust were acidified in laboratory experiments which simulate atmospheric conditions. Aerosol acidification links bioavailable phosphorus supply to anthropogenic and natural acidic gas emissions, and may be a key regulator of ocean biogeochemistry.
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