Detectability of the potential climate change effect on transboundary air pollution pathways in the downwind area of China.

Long-term aerosol optical depth (AOD) datasets focused on the Pacific Ocean in the downwind area of China over a 19-year period from 2003 to 2021 were derived from satellite observations, reanalysis datasets, and numerical simulations. Considering the significant year-to-year changes in the amounts of aerosols transported from China to the Pacific Ocean during this period, we proposed a metric named RAOD. This is defined as the AOD over the ocean relative to that near the eastern coast of China within the same latitude band (25-30°N). RAOD was identified as a valuable metric for quantifying the long-term changes in transboundary air pollution pathways. Our analysis revealed a clear exponential decrease in RAOD values from China toward the Pacific Ocean; this was consistent with the prevailing meteorological conditions observed over the 19-year period. However, the possible long-term changes in RAOD due to climate change were found to be insignificant and were overshadowed by much larger year-to-year variations in the meteorological field. Additionally, significant seasonal variations in the absolute slope of the linear regression between RAOD and longitude were observed, and there correlated with wind patterns in the lower troposphere. Elevated slope values in the spring and winter suggested a west-to-east aerosol transport facilitated by strong winds, whereas the lower slope values in summer and autumn indicated a northward aerosol movement under weaker winds. In recent years, aerosols have become less likely to be transported far eastward from the coast of China. Based on these findings, to enhance the detectability of the climate change impacts on meteorological field affecting transboundary air pollution pathways, the RAOD metric derived using a continued long-term satellite observation of aerosols is proposed.

Very high particulate pollution over northwest India captured by a high-density in situ sensor network.

Exposure to particulate matter less than 2.5 µm in diameter (PM2.5) is a cause of concern in cities and major emission regions of northern India. An intensive field campaign involving the states of Punjab, Haryana and Delhi national capital region (NCR) was conducted in 2022 using 29 Compact and Useful PM2.5 Instrument with Gas sensors (CUPI-Gs). Continuous observations show that the PM2.5 in the region increased gradually from < 60 µg m-3 in 6-10 October to up to 500 µg m-3 on 5-9 November, which subsequently decreased to about 100 µg m-3 in 20-30 November. Two distinct plumes of PM2.5 over 500 µg m-3 are tracked from crop residue burning in Punjab to Delhi NCR on 2-3 November and 10-11 November with delays of 1 and 3 days, respectively. Experimental campaign demonstrates the advantages of source region observations to link agricultural waste burning and air pollution at local to regional scales.

Classification of MODIS fire emission data based on aerosol absorption Angstrom exponent retrieved from AERONET data.

Biomass burning emits a large quantity of gaseous pollutants and aerosols into the atmosphere, which perturbs the regional and global climate and has significant impacts on air quality and human health. In order to understand the temporal and spatial distributions of biomass burning and its contribution to aerosol optical and radiative impacts, we examined fire emission data and its contribution to aerosol optical and radiative impacts over six major hot-spot continents/sub-continents across the globe, namely North-Central (NC) Africa, South America, US-Hawaii, South Asia, South East Asia, and Australia-New Zealand, using long-term satellites, ground-based and re-analysis data during 2000-2021. The selected six sites contributed ∼70% of total global fire data. The classification of biomass burning, such as pre, active, and post burning phases, was performed based on the Absorption Angstrom Exponent (AAE) estimated from 55 AERONET (AErosol RObotic NETwork) stations. The study found the highest contribution of fire count (55 %) during the active burning phase followed by post (36 %) and pre (8 %) burning phases. Such high fire counts were associated with high absorption aerosol optical depth (AAOD) during the active fire event. Strong dominance of fine and coarse mode mixed aerosols were also observed during active and post fire regimes. High AAOD and low Extinction Angstrom Exponent (EAE) over NC Africa during the fire events suggested presence of mineral dust mixed with biomass burning aerosols. Brightness temperature, fire radiative power and fire count were also dominated by the active burning followed by post and pre burning phases. The maximum heating rate of 3.15 K day-1 was observed during the active fire events. The heating rate profile shows clear variations for three different fire regimes with the highest value of 1.80 K day-1 at ∼750 hPa altitude during the active fire event.

Increased aerosols can reverse Twomey effect in water clouds through radiative pathway.

Aerosols play important roles in modulations of cloud properties and hydrological cycle by decreasing the size of cloud droplets with the increase of aerosols under the condition of fixed liquid water path, which is known as the first aerosol indirect effect or Twomey-effect or microphysical effect. Using high-quality aerosol data from surface observations and statistically decoupling the influence of meteorological factors, we show that highly loaded aerosols can counter this microphysical effect through the radiative effect to result both the decrease and increase of cloud droplet size depending on liquid water path in water clouds. The radiative effect due to increased aerosols reduces the moisture content, but increases the atmospheric stability at higher altitudes, generating conditions favorable for cloud top entrainment and cloud droplet coalescence. Such radiatively driven cloud droplet coalescence process is relatively stronger in thicker clouds to counter relatively weaker microphysical effect, resulting the increase of cloud droplet size with the increase of aerosol loading; and vice-versa in thinner clouds. Overall, the study suggests the prevalence of both negative and positive relationships between cloud droplet size and aerosol loading in highly polluted regions.

Nitrogen oxides concentration and emission change detection during COVID-19 restrictions in North India.

COVID-19 related restrictions lowered particulate matter and trace gas concentrations across cities around the world, providing a natural opportunity to study effects of anthropogenic activities on emissions of air pollutants. In this paper, the impact of sudden suspension of human activities on air pollution was analyzed by studying the change in satellite retrieved NO2 concentrations and top-down NOx emission over the urban and rural areas around Delhi. NO2 was chosen for being the most indicative of emission intensity due to its short lifetime of the order of a few hours in the planetary boundary layer. We present a robust temporal comparison of Ozone Monitoring Instrument (OMI) retrieved NO2 column density during the lockdown with the counterfactual baseline concentrations, extrapolated from the long-term trend and seasonal cycle components of NO2 using observations during 2015 to 2019. NO2 concentration in the urban area of Delhi experienced an anomalous relative change ranging from 60.0% decline during the Phase 1 of lockdown (March 25-April 13, 2020) to 3.4% during the post-lockdown Phase 5. In contrast, we find no substantial reduction in NO2 concentrations over the rural areas. To segregate the impact of the lockdown from the meteorology, weekly top-down NOx emissions were estimated from high-resolution TROPOspheric Monitoring Instrument (TROPOMI) retrieved NO2 by accounting for horizontal advection derived from the steady state continuity equation. NOx emissions from urban Delhi and power plants exhibited a mean decline of 72.2% and 53.4% respectively in Phase 1 compared to the pre-lockdown business-as-usual phase. Emission estimates over urban areas and power-plants showed a good correlation with activity reports, suggesting the applicability of this approach for studying emission changes. A higher anomaly in emission estimates suggests that comparison of only concentration change, without accounting for the dynamical and photochemical conditions, may mislead evaluation of lockdown impact. Our results shall also have a broader impact for optimizing bottom-up emission inventories.