Lagrangian particle dispersion models (LPDMs) in backward mode are widely used to quantify the impact of transboundary pollution on downwind sites. Most LPDM applications count particles with a technique that introduces a so-called footprint layer (FL) with constant height, in which passing air tracer particles are assumed to be affected by surface emissions. The mixing layer dynamics are represented by the underlying meteorological model. This particle counting technique implicitly assumes that the atmosphere is well mixed in the FL. We have performed backward trajectory simulations with the FLEXPART model starting at Cyprus to calculate the sensitivity to emissions of upwind pollution sources. The emission sensitivity is used to quantify source contributions at the receptor and support the interpretation of ground measurements carried out during the CYPHEX campaign in July 2014. Here we analyse the effects of different constant and dynamic FL height assumptions. The results show that calculations with FL heights of 100 and 300 m yield similar but still discernible results. Comparison of calculations with FL heights constant at 300 m and dynamically following the planetary boundary layer (PBL) height exhibits systematic differences, with daytime and night-time sensitivity differences compensating for each other. The differences at daytime when a well-mixed PBL can be assumed indicate that residual inaccuracies in the representation of the mixing layer dynamics in the trajectories may introduce errors in the impact assessment on downwind sites. Emissions from vegetation fires are mixed up by pyrogenic convection which is not represented in FLEXPART. Neglecting this convection may lead to severe over- or underestimations of the downwind smoke concentrations. Introducing an extreme fire source from a different year in our study period and using fire-observation-based plume heights as reference, we find an overestimation of more than 60 % by the constant FL height assumptions used for surface emissions. Assuming a FL that follows the PBL may reproduce the peak of the smoke plume passing through but erroneously elevates the background for shallow stable PBL heights. It might thus be a reasonable assumption for open biomass burning emissions wherever observation-based injection heights are not available.

Active fire observations with satellite instruments exhibit a well-documented increase of the detection threshold with increasing pixel footprint size, i.e., distance from the sub-satellite point. This results in a viewing angle-dependent, negative bias in gridded representations of the observed Fire Radiative Power (FRP), which in turn is frequently being used for climate monitoring of biomass burning and for pyrogenic emission inventories. We present a method based on quantile mapping to alleviate this bias and apply it to the gridded-FRP from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instruments. The gridded-FRP observations are corrected with a correction function that depends on the satellite viewing angle and the magnitude of FRP in each grid cell. Assuming the fire observations at nadir to be the best representation of the truth, we derive a correction function by mapping cumulative distribution function (CDF) of off-nadir gridded-FRP to the CDF of near-nadir gridded-FRP. The method can be directly applied to correct the negative bias in gridded-FRP observations at a grid resolution of $1^{\circ }$ or more. The performance of the correction methodology is confirmed through comparisons with co-located Visible Infrared Imaging Radiometer Suite (VIIRS) satellite observations: After bias correction, the gridded-FRP observations from both satellites agree better than before, particularly over savanna, tropical forests, and extra-tropical forests. Experiments with the Global Fire Assimilation System (GFAS) show that the impacts of the bias-corrected MODIS/Aqua gridded-FRP observations and VIIRS/Suomi-NPP gridded-FRP observations on regional FRP analyses are comparable, which confirms the potential for improving fire emission inventories and climate monitoring based on FRP.

Lagrangian particle dispersion models (LPDMs) in backward mode are widely-used to quantify the impact of transboundary pollution on downwind sites. Most LPDM applications assume mixing of surface emissions in a boundary layer that is constant in height. The height of this mixing layer (ML), however, is subject to strong spatio-temporal variability. Neglecting this variability may introduce substantial errors in the quantification of source contributions. Here, we perform backward trajectory simulations with the FLEXPART model starting at Cyprus to quantify these errors. The simulations calculate the sensitivity to emissions of upwind pollution sources within the ML height. The emission sensitivity is used to quantify source contributions at the receptor and support the interpretation of ground measurements carried out during the CYPHEX campaign in July 2014. It is determined by two interacting factors: the dilution of pollutants within the ML and the number of trajectories impacted by the emissions. In this study, we calculate the emission sensitivity for a constant ML height of 300 m and a dynamical ML height to compare the resulting differences. The results show that the impact of emission sources is predominantly overestimated by the neglected dilution in expanded daytime ML heights. There is, however, substantial variability in the simulated differences. For shallow marine or nocturnal ML heights, for example, a ML assumed to high may lead to an underestimation of the intensive concentrations. This variability is predominantly caused by the spatio-temporal changes in ML heights and the meteorological conditions that drive the dispersion of the trajectories. In an application example, the impact of CO emissions from hypothetical forest fires is simulated and source contributions are compared for different ML heights. The resulting difference shows that the 300 m overestimates the total CO contributions from upwind sources by 16 %. Thus, it is recommended to generally implement a dynamic mixing layer height parametrization in LPDMs to prevent these errors.