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Responses to the COVID-19 outbreak resulted in one of the largest short-term decreases in anthropogenic emissions in modern history. To date, there has been no comprehensive assessment of the impact of lockdowns on air quality and human health. Using global satellite observations and ground measurements from 36 countries in Europe, North America, and East Asia, we find that lockdowns led to reductions in NO₂ concentrations globally, resulting in ~32,000 avoided premature mortalities, including ~21,000 in China. However, we do not find corresponding reductions in PM[subscript 2.5] and ozone globally. Using satellite measurements, we show that the disconnect between NO₂ and ozone changes stems from local chemical regimes. The COVID-related lockdowns demonstrate the need for targeted air quality policies to reduce the global burden of air pollution, especially related to secondary pollutants.

Laser-induced breakdown spectroscopy (LIBS) was employed to predict the sodium content of infant formula (IF) over the range 0.5–4 mg Na g−1. Calibration models were built using partial least squares regression (PLS), correlating the LIBS spectral data with reference Na content quantified by atomic absorption spectroscopy (AAS). The main aim of this study was to demonstrate the ability of LIBS as a rapid tool for quantifying sodium in IF, but also to explore strategies concerning the acquisition and pre-processing of LIBS spectra. A range of different pre-processing techniques, measuring depths (repetition of laser shots) and accumulations were conducted and evaluated in terms of PLS performance. The best calibration model was developed using the third-layer spectra normalised by the H I 656.29 nm emission line, yielding a coefficient of determination (R2) of 0.93, and root-mean-square errors (RMSE) of 0.37 and 0.13 mg g−1 for cross-validation and validation, respectively.

Laser-induced breakdown spectroscopy (LIBS) was employed to predict the sodium content of infant formula (IF) over the range 0.5–4 mg Na g−1. Calibration models were built using partial least squares regression (PLS), correlating the LIBS spectral data with reference Na content quantified by atomic absorption spectroscopy (AAS). The main aim of this study was to demonstrate the ability of LIBS as a rapid tool for quantifying sodium in IF, but also to explore strategies concerning the acquisition and pre-processing of LIBS spectra. A range of different pre-processing techniques, measuring depths (repetition of laser shots) and accumulations were conducted and evaluated in terms of PLS performance. The best calibration model was developed using the third-layer spectra normalised by the H I 656.29 nm emission line, yielding a coefficient of determination (R2) of 0.93, and root-mean-square errors (RMSE) of 0.37 and 0.13 mg g−1 for cross-validation and validation, respectively.

Laser-induced breakdown spectroscopy (LIBS) was employed to predict the sodium content of infant formula (IF) over the range 0.5–4 mg Na g−1. Calibration models were built using partial least squares regression (PLS), correlating the LIBS spectral data with reference Na content quantified by atomic absorption spectroscopy (AAS). The main aim of this study was to demonstrate the ability of LIBS as a rapid tool for quantifying sodium in IF, but also to explore strategies concerning the acquisition and pre-processing of LIBS spectra. A range of different pre-processing techniques, measuring depths (repetition of laser shots) and accumulations were conducted and evaluated in terms of PLS performance. The best calibration model was developed using the third-layer spectra normalised by the H I 656.29 nm emission line, yielding a coefficient of determination (R2) of 0.93, and root-mean-square errors (RMSE) of 0.37 and 0.13 mg g−1 for cross-validation and validation, respectively.