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A 4-year data set of MAX-DOAS observations in the Beijing area (2008–2012) is analysed with a focus on NO2, HCHO and aerosols. Two very different retrieval methods are applied. Method A describes the tropospheric profile with 13 layers and makes use of the optimal estimation method. Method B uses 2–4 parameters to describe the tropospheric profile and an inversion based on a least-squares fit. For each constituent (NO2, HCHO and aerosols) the retrieval outcomes are compared in terms of tropospheric column densities, surface concentrations and "characteristic profile heights" (i.e. the height below which 75% of the vertically integrated tropospheric column density resides). We find best agreement between the two methods for tropospheric NO2 column densities, with a standard deviation of relative differences below 10%, a correlation of 0.99 and a linear regression with a slope of 1.03. For tropospheric HCHO column densities we find a similar slope, but also a systematic bias of almost 10% which is likely related to differences in profile height. Aerosol optical depths (AODs) retrieved with method B are 20% high compared to method A. They are more in agreement with AERONET measurements, which are on average only 5% lower, however with considerable relative differences (standard deviation ~ 25%). With respect to near-surface volume mixing ratios and aerosol extinction we find considerably larger relative differences: 10 ± 30, ?23 ± 28 and ?8 ± 33% for aerosols, HCHO and NO2 respectively. The frequency distributions of these near-surface concentrations show however a quite good agreement, and this indicates that near-surface concentrations derived from MAX-DOAS are certainly useful in a climatological sense. A major difference between the two methods is the dynamic range of retrieved characteristic profile heights which is larger for method B than for method A. This effect is most pronounced for HCHO, where retrieved profile shapes with method A are very close to the a p, Geoscience & Remote Sensing, Civil Engineering and Geosciences

A 4-year data set of MAX-DOAS observations in the Beijing area (2008-2012) is analysed with a focus on NO2, HCHO and aerosols. Two very different retrieval methods are applied. Method A describes the tropospheric profile with 13 layers and makes use of the optimal estimation method. Method B uses 2-4 parameters to describe the tropospheric profile and an inversion based on a least-squares fit. For each constituent (NO2, HCHO and aerosols) the retrieval outcomes are compared in terms of tropospheric column densities, surface concentrations and "characteristic profile heights" (i.e. the height below which 75% of the vertically integrated tropospheric column density resides). We find best agreement between the two methods for tropospheric NO2 column densities, with a standard deviation of relative differences below 10%, a correlation of 0.99 and a linear regression with a slope of 1.03. For tropospheric HCHO column densities we find a similar slope, but also a systematic bias of almost 10% which is likely related to differences in profile height. Aerosol optical depths (AODs) retrieved with method B are 20% high compared to method A. They are more in agreement with AERONET measurements, which are on average only 5% lower, however with considerable relative differences (standard deviation ∼ 25%). With respect to near-surface volume mixing ratios and aerosol extinction we find considerably larger relative differences: 10 ± 30, -23 ± 28 and -8 ± 33% for aerosols, HCHO and NO2 respectively. The frequency distributions of these near-surface concentrations show however a quite good agreement, and this indicates that near-surface concentrations derived from MAX-DOAS are certainly useful in a climatological sense. A major difference between the two methods is the dynamic range of retrieved characteristic profile heights which is larger for method B than for method A. This effect is most pronounced for HCHO, where retrieved profile shapes with method A, Atmospheric Remote Sensing

A 4-year data set of MAX-DOAS observations in the Beijing area (2008-2012) is analysed with a focus on NO2, HCHO and aerosols. Two very different retrieval methods are applied. Method A describes the tropospheric profile with 13 layers and makes use of the optimal estimation method. Method B uses 2-4 parameters to describe the tropospheric profile and an inversion based on a least-squares fit. For each constituent (NO2, HCHO and aerosols) the retrieval outcomes are compared in terms of tropospheric column densities, surface concentrations and "characteristic profile heights" (i.e. the height below which 75% of the vertically integrated tropospheric column density resides). We find best agreement between the two methods for tropospheric NO2 column densities, with a standard deviation of relative differences below 10%, a correlation of 0.99 and a linear regression with a slope of 1.03. For tropospheric HCHO column densities we find a similar slope, but also a systematic bias of almost 10% which is likely related to differences in profile height. Aerosol optical depths (AODs) retrieved with method B are 20% high compared to method A. They are more in agreement with AERONET measurements, which are on average only 5% lower, however with considerable relative differences (standard deviation ∼ 25%). With respect to near-surface volume mixing ratios and aerosol extinction we find considerably larger relative differences: 10 ± 30, -23 ± 28 and -8 ± 33% for aerosols, HCHO and NO2 respectively. The frequency distributions of these near-surface concentrations show however a quite good agreement, and this indicates that near-surface concentrations derived from MAX-DOAS are certainly useful in a climatological sense. A major difference between the two methods is the dynamic range of retrieved characteristic profile heights which is larger for method B than for method A. This effect is most pronounced for HCHO, where retrieved profile shapes with method A, Atmospheric Remote Sensing

A 4-year data set of MAX-DOAS observations in the Beijing area (2008–2012) is analysed with a focus on NO2, HCHO and aerosols. Two very different retrieval methods are applied. Method A describes the tropospheric profile with 13 layers and makes use of the optimal estimation method. Method B uses 2–4 parameters to describe the tropospheric profile and an inversion based on a least-squares fit. For each constituent (NO2, HCHO and aerosols) the retrieval outcomes are compared in terms of tropospheric column densities, surface concentrations and "characteristic profile heights" (i.e. the height below which 75% of the vertically integrated tropospheric column density resides). We find best agreement between the two methods for tropospheric NO2 column densities, with a standard deviation of relative differences below 10%, a correlation of 0.99 and a linear regression with a slope of 1.03. For tropospheric HCHO column densities we find a similar slope, but also a systematic bias of almost 10% which is likely related to differences in profile height. Aerosol optical depths (AODs) retrieved with method B are 20% high compared to method A. They are more in agreement with AERONET measurements, which are on average only 5% lower, however with considerable relative differences (standard deviation ~ 25%). With respect to near-surface volume mixing ratios and aerosol extinction we find considerably larger relative differences: 10 ± 30, ?23 ± 28 and ?8 ± 33% for aerosols, HCHO and NO2 respectively. The frequency distributions of these near-surface concentrations show however a quite good agreement, and this indicates that near-surface concentrations derived from MAX-DOAS are certainly useful in a climatological sense. A major difference between the two methods is the dynamic range of retrieved characteristic profile heights which is larger for method B than for method A. This effect is most pronounced for HCHO, where retrieved profile shapes with method A are very close to the a p, Geoscience & Remote Sensing, Civil Engineering and Geosciences

A four year data set of MAX-DOAS observations in the Beijing area (2008–2012) is analysed with a focus on NO2, HCHO, and aerosols. Two very different retrieval methods are applied. Method A describes the tropospheric profile with 13 layers and makes use of the optimal estimation method. Method B uses 2–4 parameters to describe the tropospheric profile and an inversion based on a least-squares fit. For each constituent (NO2, HCHO and aerosols) the retrieval outcomes are compared in terms of tropospheric columns, surface concentrations, and "characteristic profile heights" (i.e. the height below which 75% of the vertically integrated tropospheric column resides). We find best agreement between the two methods for tropospheric NO2 columns, with a standard deviation of relative differences below 10%, a correlation of 0.99 and a linear regression with a slope of 1.03. For tropospheric HCHO columns we find a similar slope, but also a systematic bias of almost 10% which is likely related to differences in profile height. Aerosol optical depths (AODs) retrieved with method B are 20% high compared to method A. They are more in agreement with AERONET measurements, which are on average only 5% lower, however with considerable relative differences (standard deviation ~25%). With respect to near surface volume mixing ratios and aerosol extinction we find considerably larger relative differences: 10 ± 30%, ?23 ± 28% and ?8 ± 33% for aerosols, HCHO and NO2 respectively. The frequency distributions of these near-surface concentrations show however a quite good agreement, and this indicates that near-surface concentrations derived from MAX-DOAS are certainly useful in a climatological sense. A major difference between the two methods is the dynamic range of retrieved characteristic profile heights which is larger for method B than for method A. This effect is most pronounced for HCHO, where retrieved profile shapes with method A are very close to the a priori, and moderate for NO2 a, Geoscience & Remote Sensing, Civil Engineering and Geosciences

Ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements of nitrous acid (HONO) and its precursor NO2 (nitrogen dioxide) as well as aerosols have been performed daily in Beijing city centre (39.98° N, 116.38° E) from July 2008 to April 2009 and at the suburban site of Xianghe (39.75° N, 116.96° E) located ~60 km east of Beijing from March 2010 to December 2012. This extensive dataset allowed for the first time the investigation of the seasonal cycle of HONO as well as its diurnal variation in and in the vicinity of a megacity. Our study was focused on the HONO and NO2 near-surface concentrations (0–200 m layer) and total vertical column densities (VCDs) and also aerosol optical depths (AODs) and extinction coefficients retrieved by applying the Optimal Estimation Method to the MAX-DOAS observations. Monthly averaged HONO near-surface concentrations at local noon display a strong seasonal cycle with a maximum in late fall/winter (~0.8 and 0.7 ppb at Beijing and Xianghe, respectively) and a minimum in summer (~0.1 ppb at Beijing and 0.03 ppb at Xianghe). The seasonal cycles of HONO and NO2 appear to be highly correlated, with correlation coefficients in the 0.7–0.9 and 0.5–0.8 ranges at Beijing and Xianghe, respectively. The stronger correlation of HONO with NO2 and also with aerosols observed in Beijing suggests possibly larger role of NO2 conversion into HONO in the Beijing city center than at Xianghe. The observed diurnal cycle of HONO near-surface concentration shows a maximum in the early morning (about 1 ppb at both sites) likely resulting from night-time accumulation, followed by a decrease to values of about 0.1–0.4 ppb around local noon. The HONO / NO2 ratio shows a similar pattern with a maximum in the early morning (values up to 0.08) and a decrease to ~0.01–0.02 around local noon. The seasonal and diurnal cycles of the HONO near-surface concentration are found to be similar in shape and in relative amplitude to the corre, Geoscience & Remote Sensing, Civil Engineering and Geosciences

A four year data set of MAX-DOAS observations in the Beijing area (2008–2012) is analysed with a focus on NO2, HCHO, and aerosols. Two very different retrieval methods are applied. Method A describes the tropospheric profile with 13 layers and makes use of the optimal estimation method. Method B uses 2–4 parameters to describe the tropospheric profile and an inversion based on a least-squares fit. For each constituent (NO2, HCHO and aerosols) the retrieval outcomes are compared in terms of tropospheric columns, surface concentrations, and "characteristic profile heights" (i.e. the height below which 75% of the vertically integrated tropospheric column resides). We find best agreement between the two methods for tropospheric NO2 columns, with a standard deviation of relative differences below 10%, a correlation of 0.99 and a linear regression with a slope of 1.03. For tropospheric HCHO columns we find a similar slope, but also a systematic bias of almost 10% which is likely related to differences in profile height. Aerosol optical depths (AODs) retrieved with method B are 20% high compared to method A. They are more in agreement with AERONET measurements, which are on average only 5% lower, however with considerable relative differences (standard deviation ~25%). With respect to near surface volume mixing ratios and aerosol extinction we find considerably larger relative differences: 10 ± 30%, ?23 ± 28% and ?8 ± 33% for aerosols, HCHO and NO2 respectively. The frequency distributions of these near-surface concentrations show however a quite good agreement, and this indicates that near-surface concentrations derived from MAX-DOAS are certainly useful in a climatological sense. A major difference between the two methods is the dynamic range of retrieved characteristic profile heights which is larger for method B than for method A. This effect is most pronounced for HCHO, where retrieved profile shapes with method A are very close to the a priori, and moderate for NO2 a, Geoscience & Remote Sensing, Civil Engineering and Geosciences

Ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements of nitrous acid (HONO) and its precursor NO2 (nitrogen dioxide) as well as aerosols have been performed daily in Beijing city centre (39.98° N, 116.38° E) from July 2008 to April 2009 and at the suburban site of Xianghe (39.75° N, 116.96° E) located ~60 km east of Beijing from March 2010 to December 2012. This extensive dataset allowed for the first time the investigation of the seasonal cycle of HONO as well as its diurnal variation in and in the vicinity of a megacity. Our study was focused on the HONO and NO2 near-surface concentrations (0–200 m layer) and total vertical column densities (VCDs) and also aerosol optical depths (AODs) and extinction coefficients retrieved by applying the Optimal Estimation Method to the MAX-DOAS observations. Monthly averaged HONO near-surface concentrations at local noon display a strong seasonal cycle with a maximum in late fall/winter (~0.8 and 0.7 ppb at Beijing and Xianghe, respectively) and a minimum in summer (~0.1 ppb at Beijing and 0.03 ppb at Xianghe). The seasonal cycles of HONO and NO2 appear to be highly correlated, with correlation coefficients in the 0.7–0.9 and 0.5–0.8 ranges at Beijing and Xianghe, respectively. The stronger correlation of HONO with NO2 and also with aerosols observed in Beijing suggests possibly larger role of NO2 conversion into HONO in the Beijing city center than at Xianghe. The observed diurnal cycle of HONO near-surface concentration shows a maximum in the early morning (about 1 ppb at both sites) likely resulting from night-time accumulation, followed by a decrease to values of about 0.1–0.4 ppb around local noon. The HONO / NO2 ratio shows a similar pattern with a maximum in the early morning (values up to 0.08) and a decrease to ~0.01–0.02 around local noon. The seasonal and diurnal cycles of the HONO near-surface concentration are found to be similar in shape and in relative amplitude to the corre, Geoscience & Remote Sensing, Civil Engineering and Geosciences