This work introduces the results of an intensive 15-day surface observation campaign of methane (CH4) and adapts a new analytical method to compute and attribute CH4 emissions. The selected area has a high atmospheric concentration of CH4 (campaign-wide minimum/mean/standard deviation/max observations: 2.0, 2.9, 1.3, and 16 ppm) due to a rapid increase in the mining, production, and use of coal over the past decade. Observations made in concentric circles at 1km, 3km, and 5km around a high production high gas coal mine were used with the mass conserving model free emissions estimation approach adapted to CH4, yielding emissions of 0.73, 0.28, and 0.15 ppm/min respectively. Attribution used a 2-box mass conserving model to identify the known mine’s emissions from 0.042-5.3 ppm/min, and a previously unidentified mine’s emission from 0.22-7.9 ppm/min. These results demonstrate the importance of quantifying the spatial distribution of methane in terms of control of regional-scale CH4 emissions.

This work addresses the relationship between major dynamical forcings and variability in NO column measurements. The dominating impact on Siberia is due to El Niño, on Indonesia, Northern Australia and South America is due to IOD,and on the remaining regions is due to NAO. That NO pollution in Indonesia is modulated by IOD contradicts previous work using AOD and El Niño. Simultaneous impacts of present and lagged forcings are derived using multi-linear regression, demonstrating El Niño impacts NO variability from 7 to 98 weeks ahead, while IOD and NAO are mostly impacted by past changes in NO variability. In all cases, lagged forcings exhibit more impact than present forcings, hinting at non-linearity. Finally, dynamical forcings are responsible for over 50% of the NO variability in most non-urban areas and over 40% in urban Indonesia and China. These results demonstrate the significance of climate forcing on short-lived air pollutants.

The contribution of biomass burning to the total aerosol loading over Monsoon Asia is both significant while also continuing to increase in recent decades. To better match the spatio-temporal distribution of aerosols and trace gasses observed in the free troposphere, this work applied a 3-D constrained emission inventory based on top-down remotely sensed NO2 measurement to investigate the most extreme of the annually occurring biomass burning seasons in Monsoon Asia. In 2016 this constituted an extreme event observed over a 6-day period covering millions of square kilometers, including over regions which are typically in the rainy phase of the Monsoon at this time. The results are shown to be consistent with respect to TRMM precipitation, AERONET measurements, MODIS AOD, MOPITT CO, and reanalysis meteorology, over both the biomass burning source as well as the millions of square kilometers downwind both to the East and to the Southwest. Reproducing the observed long-range transport pattern requires the time of biomass burning to be increased, regions not previously identified as burning to be actual source regions, and the emissions of BC to be 6.6 to 11.9 time larger than current inventories. The underlying mechanism for this long-range transport involves a new 3-D pathway that can occur during the transition from the North to the South Monsoon. The results are also consistent with the new idea that large loadings of BC in the lower free troposphere may significantly affect the meteorological field and the overall vertical distribution of aerosols in the tropical troposphere.

Absorbing aerosols uniquely impact radiative forcing, aerosol chemical transport, and meteorology. This paper uniquely quantifies BC core and sulfate shell size and mass using decadal measurements of multi-spectral AOD, SSA, and AE from AERONET stations located throughout East, Southeast, and South Asia, in connection with a MIE model. All sites are uniquely characterized into four types: urban, biomass burning, long-range transport, and clean. The size and mass of the core and shell are calculated as probability distributions, and found to be unique within each classification. Well known urban, biomass burning, and clean sites are all properly identified. Furthermore, two unique sites previously thought to not have multiple characteristics are identified, with urban and biomass burning significant in Beijing and long-range transport significant in the otherwise clean South China Sea at Taiping island. It is hoped that these results will allow for advances in attribution and radiative forcing studies.

Energy, transport, urbanization and burning are responsible for changes in atmospheric BC. This work uses direct solar atmospheric column measurements of single scatter albedo [SSA] retrieved at multiple wavelengths from AERONET at 68 Asian sites over 17 years. A MIE model is solved across the wavelengths using a core-shell mixing approximation to invert the probabilistic BC, shell size, and UV SSA. Orthogonal patterns are obtained for urban, biomass burning [BB], and long-range transport [LRT] conditions, which are used to analyze and attribute source types of BC across the region. Large urban areas (thought to be dominated by urban BC) are observations during targeted times (shorter than seasonally) to yield significant contributions from non-urban BC. BB and LRT are observed to dominate Beijing and Hong Kong 2 months a year. LRT is observed during the clean Asian Monsoon season in both Nepal and Hong Kong, with sources identified from thousands of kilometers away. Computing the shift in shell size required to constrain the results approximates secondary aerosol growth in-situ, and subsequently aerosol lifetime, which is found to range from 11 days to a month, implying both a significant amount of BC above the boundary layer, and that BC generally has a longer lifetime than PM2.5. These findings are outside of the range of most modeling studies focusing on PM2.5, but are consistent with independent measurements from SP2 and modeling studies of BC that use core-shell mixing together with high BC emissions.

Black carbon (BC), organic carbon (OC) and dust (or Absorbing Aerosols - AA) strongly absorb visible solar radiation, leading to impacts on the atmospheric radiation budget, climate, water cycle, and more. Recent attempts have been made to elucidate the spatial-temporal concentrations and radiative forcing of AA over East Asia using the UV band OMAERUV product from OMI. The product provides global coverage of AAOD in the UV bands, limiting the results to where retrievals can be made, and to cases where the average aerosol size is not too small. For these reasons, this approach cannot estimate the magnitude of total AAOD and/or radiative forcing. To achieve this, we include relevant data from multiple bands in the visible and NIR in tandem with the UV, so that a more complete relationship can be made to understand the magnitude and properties of AA globally. We employ a MIE model to simulate the absorption of core-shell coated mixtures of AA (specifically a mixture of BC core with sulfate shell (MBS) and OC core with sulfate shell (MOS) across multiple individual wavelengths. These values are then merged with individual inversions of SSA from AERONET at each individual wavelength across the spectrum from the UV through the NIR. Fitting is done based on the temporally varying magnitude band of the measured AOD and the inverted SSA incorporating all individual data points where both calculations exist at each station, from 2010 to 2016. The relationship between core and shell sizes that is consistent with AERONET is then fitted to OMI measurements that overlap AERONET in space and time. A sensitivity matrix of optical uncertainties is made to compute the robustness of the constrained aerosol size, chemical composition and refractive indices. Initial results show that retrieved aerosol properties of MBS and MOS are consistent with known properties over urban areas, biomass burning areas, and those regions frequently impacted by long-range transport events, as observed over Asia. A few interesting scientific findings include mixing between these different sources and detection of otherwise missing sources. It is hoped that ongoing calculations allowing our approximation to be extended spatially away from sites where AERONET measurements exist will also be ready to present.

This work constructs multiple regression equations of surface ozone concentration based on non-linear combinations of high temporal frequency and multi-year measurements of air pollutant concentrations (PM2.5, CO, NO2, SO2) and remotely sensed ultraviolet Index (UVI) in nine different urban regions in China. These nine regions all have different emissions profiles, economic drivers, and climatology, allowing a more rigorous investigation of the factors most responsible to local surface ozone. The results show a good fit of ozone can be made temporally (including many peaks and troughs), under conditions ranging from relatively clean through polluted, with minimum and maximum bounds on the goodness of the fit usually in the range from 5 to 130 ug/m3. Overall, the results demonstrate significant differences in terms of the most important driving factors in the different cities, with UV radiation being most important in all cities, followed by CO, PM2.5, and NO2 or a combination, depending on each individual city. The performance of the ozone prediction and real measurements under both clean and polluted conditions of PM2.5 or CO mass concentrations are further explored and found to match very well in Xi’an and Beijing. Discussion is presented and supported to quantify insights into why solar ultraviolet radiation coupled with easier to measure longer-lived air pollutants contribute a significant amount to surface ozone is possible, all without needing to necessarily at first order wade into the extremely complex chemistry and physics involved with boundary layer meteorology and VOC chemistry.

Nitrogen oxides (NOx) are markers of combustion contributing to ozone, secondary aerosol, and acid rain, and are required to run models focusing on atmospheric environmental protection. This work presents a new model free inversion estimation framework using daily TROPOMI NO2 columns and observed fluxes from the continuous emissions monitoring systems (CEMS) to quantify emissions of NOx at 0.05°×0.05°. The average emission is 0.72±0.11Tg/yr from 2019 through 2021 over Shanxi, a major energy producing and consuming province in Northern China. The resulting emissions demonstrates significant spatial and temporal differences with bottom-up emissions databases, with 54% of the emissions concentrated in 25% of the total area. Two major forcing factors are horizontal advective transport (352.0±51.2km) and first order chemical loss (13.1±1.1hours), consistent with a non-insignificant amount of NOxadvected into the free troposphere. The third forcing factor, the computed ratio of NOx/NO2, on a pixel-by-pixel basis has a significant correlation with the combustion temperature and energy efficiency of large energy consuming sources. Specifically, thermal power plants, cement, and iron and steel companies have high NOx/NO2 ratios, while coking, industrial boilers, and aluminum show low ratios. Variance maximization applied to the daily TROPOMI NO2 columns identifies three modes dominate the variance and attributes them to this work’s computed emissions, remotely sensedTROPOMI UVAI, and transport based on TROPOMI CO. Using satellite observations for emission estimates in connection with CEMS allows the rapid update of emissions, while also providing scientific support for the identification and attribution of anthropogenic sources.

People spend most of their time indoors, and therefore exposure to aerosols and precursor-gasses in the indoor environment is of extreme concern with respect to people’s health, well-being, working efficiency, and overall life quality. Such sources include both those emitted inside as well as those which may intrude from the outside. To better quantify and understand these sources and their impacts we employ multiple air quality monitors and simple models, both within and outside of various residential environments located in different cities of different development levels in China. To enhance the livability of the indoor environment, we further work to quantify two newly relevant factors: portable indoor aerosol filters and the idea of “increased ventilation”. The combined goal of this work is to understand the combination of factors leading to an improvement in Indoor Air Quality (IAQ), including but not limited to: mass transfer to/from the indoor environment, removal and/or enhancement due to the filters and ventilation, removal from the room itself, emissions, and other possible non-linearities not accounted for on this list. Concentrations of aerosols across different sizes from 0.3um to 10um are measured and analyzed at 2-minute intervals over a minimum of 20 days, allowing for an analysis that encompasses all of the possibilities of natural and anthropogenic variability typically encountered in a real environment. This includes analysis both with and without filters, under extreme outdoor loading conditions, with intense indoor emissions sources, pseudo-equilibrium conditions, and measurements made during different meteorological events, both with and without high rates of indoor to outdoor air exchange. Results show that the impacts are relatively large under both equilibrium and high event conditions, include both the magnitude of the drop as well as the time taken to achieve the reduction. A further conclusion is that increased ventilation may lead to a worsening of IAQ. A final conclusion is that larger particles more likely associated with PM2.5 are removed at a different rate from much smaller particles more associated with PM0.5 or PM1.

Current approaches to estimate NOx emissions fail to account for new and small sources, biomass burning, and sources which change rapidly in time, generally don’t account for measurement error, and are either based on models, or do not consider wind, chemistry, and dynamical effects. This work introduces a new, model-free analytical environment that assimilates daily TROPOMI NO2 measurements in a mass-conserving manner, to invert daily NOx emissions. This is applied over a rapidly developing and energy-consuming region of Northwest China, specifically chosen due to substantial economic and population changes, new environmental policies, large use of coal, and access to independent emissions measurements for validation, making this region representative of many rapidly developing regions found across the Global South. This technique computes a net NOx emissions gain of 70% distributed in a seesaw manner: a more than doubling of emissions in cleaner regions, chemical plants, and regions thought to be emissions-free, combined with a more than halving of emissions in city centers and at well-regulated steel and powerplants. The results allow attribution of sources, with major contributing factors computed to be increased combustion temperature, atmospheric transport, and in-situ chemical processing. It is hoped that these findings will drive a new look at emissions estimation and how it is related to remotely sensed measurements and associated uncertainties, especially applied to rapidly developing regions. This is especially important for understanding the loadings and impacts of short-lived climate forcers, and provides a bridge between remotely sensed data, measurement error, and models, while allowing for further improvement of identification of new, small, and rapidly changing sources.