Changing air pollution scenario during COVID-19: Redefining the hotspot regions over India.

The present study investigates the air pollution pattern over India during the COVID-19 lockdown period (24 March-31 May 2020), pre-lockdown (1-23 March 2020) and the same periods from 2019 using Moderate Resolution Imaging Spectroradiometer (MODIS) Terra aerosol optical depth (AOD) with level 2 (10 km × 10 km) and level 3 (1° × 1° gridded) collection 6.1 Dark Target Deep Blue (DT-DB) aerosol product the Tropospheric Monitoring Instrument (TROPOMI) NO2 and SO2 data with a spatial resolution of 7 km × 3.5 km. We also use long-term average (2000-2017) of AOD for March-May to identify existing hotspot regions and to compare the variations observed in 2019 and 2020. The aim of the present work is to identify the pollution hotspot regions in India that existed during the lockdown and understanding the future projection scenarios reported by previous studies in light of the present findings. We have incorporated Menn-Kendall trend analysis to understand the AOD trends over India and percentage change in AOD, NO2 and SO2 to identify air pollution pattern changes during the lockdown. The results indicate higher air pollution levels over eastern India over the coal-fired power plants clusters. By considering the earlier projected studies, our results suggest that eastern India will have higher levels of air pollution, making it a new hotspot region for air pollution with highest magnitudes.

Aviation effects on already-existing cirrus clouds.

Determining the effects of the formation of contrails within natural cirrus clouds has proven to be challenging. Quantifying any such effects is necessary if we are to properly account for the influence of aviation on climate. Here we quantify the effect of aircraft on the optical thickness of already-existing cirrus clouds by matching actual aircraft flight tracks to satellite lidar measurements. We show that there is a systematic, statistically significant increase in normalized cirrus cloud optical thickness inside mid-latitude flight tracks compared with adjacent areas immediately outside the tracks.

Remote sensing of aerosols in the Arctic for an evaluation of global climate model simulations.

In this study Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua retrievals of aerosol optical thickness (AOT) at 555 nm are compared to Sun photometer measurements from Svalbard for a period of 9 years. For the 642 daily coincident measurements that were obtained, MODIS AOT generally varies within the predicted uncertainty of the retrieval over ocean (ΔAOT = ±0.03 ± 0.05 · AOT). The results from the remote sensing have been used to examine the accuracy in estimates of aerosol optical properties in the Arctic, generated by global climate models and from in situ measurements at the Zeppelin station, Svalbard. AOT simulated with the Norwegian Earth System Model/Community Atmosphere Model version 4 Oslo global climate model does not reproduce the observed seasonal variability of the Arctic aerosol. The model overestimates clear-sky AOT by nearly a factor of 2 for the background summer season, while tending to underestimate the values in the spring season. Furthermore, large differences in all-sky AOT of up to 1 order of magnitude are found for the Coupled Model Intercomparison Project phase 5 model ensemble for the spring and summer seasons. Large differences between satellite/ground-based remote sensing of AOT and AOT estimated from dry and humidified scattering coefficients are found for the subarctic marine boundary layer in summer. KEY POINTS: Remote sensing of AOT is very useful in validation of climate models.

Vertical profiles of pure dust and mixed smoke-dust plumes inferred from inversion of multiwavelength Raman/polarization lidar data and comparison to AERONET retrievals and in situ observations.

We present for the first time vertical profiles of microphysical properties of pure mineral dust (largely unaffected by any other aerosol types) on the basis of the inversion of optical data collected with multiwavelength polarization Raman lidar. The data were taken during the Saharan Mineral Dust Experiment (SAMUM) in Morocco in 2006. We also investigated two cases of mixed dust-smoke plumes on the basis of data collected during the second SAMUM field campaign that took place in the Republic of Cape Verde in 2008. Following the experience of the Aerosol Robotic Network (AERONET), the dust is modeled as a mixture of spherical particles and randomly oriented spheroids. The retrieval is performed from the full set of lidar input data (three backscatter coefficients, two extinction coefficients, and one depolarization ratio) and from a reduced set of data in which we exclude the depolarization ratio. We find differences of the microphysical properties depending on what kind of optical data combination we use. For the case of pure mineral dust, the results from these two sets of optical data are consistent and confirm the validity of the spheroid particle model for data inversion. Our results indicate that in the case of pure mineral dust we do not need depolarization information in the inversion. For the mixture of dust and biomass burning, there seem to be more limitations in the retrieval accuracy of the various data products. The evaluation of the quality of our data products is done by comparing our lidar-derived data products (vertically resolved) to results from AERONET Sun photometer observations (column-averaged) carried out at the lidar field site. Our results for dust effective radius show agreement with the AERONET observations within the retrieval uncertainties. Regarding the complex refractive index a comparison is difficult, as AERONET provides this parameter as wavelength-dependent quantity. In contrast, our inversion algorithm provides this parameter as a wavelength-independent quantity. We also show some comparison to results from airborne in situobservation. A detailed comparison to in situ results will be left for a future contribution.

Systematic error of lidar profiles caused by a polarization-dependent receiver transmission: quantification and error correction scheme.

Signals of many types of aerosol lidars can be affected with a significant systematic error, if depolarizing scatterers are present in the atmosphere. That error is caused by a polarization-dependent receiver transmission. In this contribution we present an estimation of the magnitude of this systematic error. We show that lidar signals can be biased by more than 20%, if linearly polarized laser light is emitted, if both polarization components of the backscattered light are measured with a single detection channel, and if the receiver transmissions for these two polarization components differ by more than 50%. This signal bias increases with increasing ratio between the two transmission values (transmission ratio) or with the volume depolarization ratio of the scatterers. The resulting error of the particle backscatter coefficient increases with decreasing backscatter ratio. If the particle backscatter coefficients are to have an accuracy better than 5%, the transmission ratio has to be in the range between 0.85 and 1.15. We present a method to correct the measured signals for this bias. We demonstrate an experimental method for the determination of the transmission ratio. We use collocated measurements of a lidar system strongly affected by this signal bias and an unbiased reference system to verify the applicability of the correction scheme. The errors in the case of no correction are illustrated with example measurements of fresh Saharan dust.

Airborne high spectral resolution lidar for measuring aerosol extinction and backscatter coefficients.

An airborne high spectral resolution lidar (HSRL) based on an iodine absorption filter and a high-power frequency-doubled Nd:YAG laser has been developed to measure backscatter and extinction coefficients of aerosols and clouds. The instrument was operated aboard the Falcon 20 research aircraft of the German Aerospace Center (DLR) during the Saharan Mineral Dust Experiment in May-June 2006 to measure optical properties of Saharan dust. A detailed description of the lidar system, the analysis of its data products, and measurements of backscatter and extinction coefficients of Saharan dust are presented. The system errors are discussed and airborne HSRL results are compared to ground-based Raman lidar and sunphotometer measurements.

Particle backscatter, extinction, and lidar ratio profiling with Raman lidar in south and north China.

Aerosol Raman lidar observations of profiles of the particle extinction and backscatter coefficients and the respective extinction-to-backscatter ratio (lidar ratio) were performed under highly polluted conditions in the Pearl River Delta (PRD) in southern China in October 2004 and at Beijing during a clear period with moderately polluted to background aerosol conditions in January 2005. The anthropogenic haze in the PRD is characterized by volume light-extinction coefficients of particles ranging from approximately 200 to 800 Mm(-1) and lidar ratios mostly between 40 and 55 sr (average of 47+/-6 sr). Almost clean air masses were observed throughout the measurements of the Beijing campaign. These air masses originated from arid desert-steppe-like regions (greater Gobi area). Extinction values usually varied between 100 and 300 Mm(-1), and the lidar ratios were considerably lower (compared with PRD values) with values mostly from 30 to 45 sr (average of 38+/-7 sr). Gobi dust partly influenced the observations. Unexpectedly low lidar ratios of approximately 25 sr were found for a case of background aerosol with a low optical depth of 0.05. The low lidar ratios are consistent with Mie-scattering calculations applied to ground-based observations of particle size distributions.

Retrieval of aerosol properties from combined multiwavelength lidar and sunphotometer measurements.

Simulation studies were carried out with regard to the feasibility of using combined observations from sunphotometer (SPM) and lidar for microphysical characterization of aerosol particles, i.e., the retrieval of effective radius, volume, and surface-area concentrations. It was shown that for single, homogeneous aerosol layers, the aerosol parameters can be retrieved with an average accuracy of 30% for a wide range of particle size distributions. Based on the simulations, an instrument combination consisting of a lidar that measures particle backscattering at 355 and 1574 nm, and a SPM that measures at three to four channels in the range from 340 to 1020 nm is a promising tool for aerosol characterization. The inversion algorithm has been tested for a set of experimental data. The comparison with the particle size distribution parameters, measured with in situ instrumentation at the lidar site, showed good agreement.