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In this study, differential game theory was applied to propose two guidance laws of a pursuer in an orbit pursuit–evasion–defense game. One was a conservative guidance law of maneuvering to absolute safety before pursuing the evader, and the other was a radical guidance law of playing with the defender only when necessary. Both guidance laws enable the pursuer to avoid the defender while pursuing the evader, but the radical guidance law reduces the pursuit time by moving the pursuer closer to the defender. The pursuer, defender, and evader are all spacecraft carrying three-axis thrusters that can provide independent thrust in three directions. The proximity dynamics processes of the participants were described by the Clohessy–Wiltshire equations. A method for solving the time-to-go analytically was proposed by simplifying the dynamics model to meet real-time requirements. The effectiveness of the two guidance laws was verified by numerical simulations, and the differences between the two laws were analyzed. [ABSTRACT FROM AUTHOR]

Nitrogen oxides (NOx = NO + NO2) play a crucial role in the formation of ozone and secondary inorganic and organic aerosols, thus affecting human health, global radiation budget, and climate. The diurnal and spatial variations in NO2 are functions of emissions, advection, deposition, vertical mixing, and chemistry. Their observations, therefore, provide useful constraints in our understanding of these factors. We employ a Regional chEmical and trAnsport model (REAM) to analyze the observed temporal (diurnal cycles) and spatial distributions of NO2 concentrations and tropospheric vertical column densities (TVCDs) using aircraft in situ measurements and surface EPA Air Quality System (AQS) observations as well as the measurements of TVCDs by satellite instruments (OMI: the Ozone Monitoring Instrument; GOME-2A: Global Ozone Monitoring Experiment – 2A), ground-based Pandora, and the Airborne Compact Atmospheric Mapper (ACAM) instrument in July 2011 during the DISCOVER-AQ campaign over the Baltimore–Washington region. The model simulations at 36 and 4 km resolutions are in reasonably good agreement with the regional mean temporospatial NO2 observations in the daytime. However, we find significant overestimations (underestimations) of model-simulated NO2 (O3) surface concentrations during nighttime, which can be mitigated by enhancing nocturnal vertical mixing in the model. Another discrepancy is that Pandora-measured NO2 TVCDs show much less variation in the late afternoon than simulated in the model. The higher-resolution 4 km simulations tend to show larger biases compared to the observations due largely to the larger spatial variations in NOx emissions in the model when the model spatial resolution is increased from 36 to 4 km. OMI, GOME-2A, and the high-resolution aircraft ACAM observations show a more dispersed distribution of NO2 vertical column densities (VCDs) and lower VCDs in urban regions than corresponding 36 and 4 km model simulations, likely reflecting the spatial distribution bias of NOx emissions in the National Emissions Inventory (NEI) 2011. [ABSTRACT FROM AUTHOR]

Measurement‐model comparisons for various atmospheric species have been widely used for evaluating the reliability of model simulations, yet such comparisons are quite limited for atmospheric isoprene due to the lack of systematic observations over a large scale. Here, we collected ambient air samples concurrently at 20 sites in China during 2012–2014 and compared the observed isoprene mixing ratios with those simulated by coupling MEGAN v2.1 with the 3‐D Regional chEmical trAnsport Model. The observed average isoprene concentration for all 1,731 samples is 0.35 ± 0.03 ppbv, 13% higher than the model simulated average of 0.31 ± 0.02 ppbv; while during the growing season, the simulated average (0.53 ± 0.05 ppbv) is almost the same as the observed average (0.52 ± 0.04 ppbv). The observed isoprene average level in the north (0.35 ppbv) is similar to that in the south (0.37 ppbv). However, the model simulated average in the south (0.53 ppbv) is ∼4 times that in the north (0.14 ppbv). The model overestimated the observations at most southern sites but underestimated at most northern sites in the growing season, which might be resulted from inadequate characterization of isoprene‐emitting land vegetation with fast afforestation in the north and rapid urbanization in the south. Compared to the model simulation, the observations revealed abnormally high isoprene levels in winter at some northern sites, largely due to nonbiogenic emissions, as evidenced by the enhancements of measured combustion tracers concurrent with the abnormally elevated isoprene levels. Plain Language Summary: Isoprene alone accounts for approximately one‐third of global emission of volatile organic compounds from both nature and human activities, yet in many parts of the world biogenic isoprene emission estimates have large uncertainties (reported isoprene emission estimates span 4–29 TgC y−1 in China), and narrowing these uncertainties is a challenging task. Here we collected ambient air samples concurrently at 20 sites over China during 2012–2014, and made measurement‐model comparison to check the emission estimates for isoprene, and found that although overall observed and predicted average isoprene levels matched well particularly during growing seasons, there exists a south‐north discrepancy that model simulated averages in the south were much higher than the north while their observed averages were quite near each other. Modeled values overestimated at most southern sites but underestimated at most northern sites, probably the fast afforestation in the north and rapid urbanization in the southeast were inadequately characterized in the model. Abnormally higher isoprene levels were observed in winter at some northern sites probably due to contribution from nonbiogenic sources. Our results highlight that high‐resolution PFT/LAI, field campaigns with higher spatial and temporal resolutions, as well as biomass burning activity data, are necessary for better observation‐model comparison. Key Points: Ambient isoprene mixing ratios observed at 20 sites across China during 2012–2014 are compared with the MEGAN‐REAM model simulationThe model simulated averages in the south were much higher than those in north, while the observed averages were much more similarAbnormally high isoprene levels were observed in winter at some northern sites probably due to contributions from nonbiogenic sources [ABSTRACT FROM AUTHOR]

High ozone concentrations have become the major summertime air quality problem in China. Extensive in situ observations are deployed for developing strategies to effectively control the emissions of ozone precursors, that is, nitrogen oxides (NOX = NO + NO2) and volatile organic compounds (VOCs). The modeling analysis of in situ observations often makes uses of the dependence of ozone peak concentration on NOX and VOC emissions, because ozone observations are among the most widely available air quality measurements. To extract more information from regulatory ozone observations, we extend the ozone‐precursor relationship to ozone peak time in this study. We find that the sensitivities of ozone peak time and concentration are complementary for regions with large anthropogenic emissions such as China. The ozone peak time is sensitive to both VOC and NOX emissions, and the sensitivity is nearly linear in the transition regime of ozone production compared to the changing ozone peak concentration sensitivity in this regime, making the diagnostics of ozone peak time particularly valuable. The extended ozone‐precursor relationships can be readily applied to understand the effects on ozone by emission changes of NOX and VOC and to assess potential biases of NOX and VOC emission inventories. These observation constraints based on regulatory ozone observations can complement the other measurement and modeling analysis methods nicely. Furthermore, we suggest that the ozone peak time sensitivity we discussed here to be used as a model evaluation measure before the empirical kinetic modeling approach (EKMA) diagram is applied to understand the effectiveness of emission control on ozone concentrations. Plain Language Summary: High ozone concentrations have become the major summertime air quality problem in China. Air quality models are routinely used to investigate effective ozone strategies by controlling the emissions of ozone precursors, nitrogen oxides (NOX = NO + NO2) and volatile organic compounds (VOCs). Therefore, the evaluations of model‐simulated sensitivities of ozone to its precursor emissions using available observations are urgently needed. In the past, efforts have been focused on sensitivities of ozone peak concentrations to its precursor emissions. We show in this work that the observations of ozone peak time can also be applied to understand ozone sensitivities to its precursor emissions, especially in regions with large anthropogenic emissions such as China. Before air quality models are applied to investigate effective strategies of controlling ozone precursor emissions, we suggest that the model simulations of ozone peak time and concentrations are evaluated using the extensive regulatory air quality monitoring network data. Model biases in simulated ozone peak time or concentrations also provide important clues to potential model errors, such as systematic biases in the estimated emissions of ozone precursors. These biases in model simulations can lead to erroneous emission control strategies and need to be corrected before air quality models can be used in policy applications. Key Points: The ozone peak time can be used similarly to ozone peak levels to evaluate ozone sensitivities to NOX and VOC emissions in model simulationsThe sensitivities of ozone peak time and concentration are complementary for regions with large anthropogenic emissionsThe biases of model‐simulated ozone peak time and concentrations provide additional constraints on NOX and VOC emission inventories [ABSTRACT FROM AUTHOR]

In this study, we evaluated the variations of air quality in Lanzhou, a typical city in Northwestern China impacted by the COVID‐19 lockdown. The mass concentration and chemical composition of non‐refractory submicron particulate matter (NR‐PM1) were determined by a high‐resolution aerosol mass spectrometer during January‐March 2020. The concentration of NR‐PM1 dropped by 50% from before to during control period. The five aerosol components (sulfate, nitrate, ammonium, chloride, and organic aerosol [OA]) all decreased during the control period with the biggest decrease observed for secondary inorganic species (70% of the total reduction). Though the mass concentration of OA decreased during the control period, its source emissions varied differently. OA from coal and biomass burning remained stable from before to during control period, while traffic and cooking related emissions were reduced by 25% and 50%, respectively. The low concentration during the control period was attributed to the lower production rate for secondary aerosols. Plain Language Summary: At the beginning of 2020, a novel coronavirus disease (COVID‐19) was spreading in China and lasting through the following months. People's outdoor activities due to the coupling effect of this epidemic and the Chinese New Year holiday were greatly reduced and pollutant emissions related with these activities were also reduced during this period. This situation provides us a unique chance to look into the air quality and evaluate the corresponding mitigation measures in the city. We observed a significant drop of the mass concentration of NR‐PM1 by 50% in Lanzhou. The reduction of NR‐PM1 was mainly from secondary inorganic species accounting for 70% of reduced NR‐PM1. This finding is significantly different from that observed in Eastern China where the mass concentration of fine particulate matter was not reduced significantly with the reduction of primary emissions due to enhanced secondary production. In contrast, the production rates for secondary inorganic and organic aerosols showed a decreasing trend from before to during control period. These results revealed the large difference in air pollution chemistry between East and West China. Key Points: The submicron aerosol mass concentration was reduced by 50% during COVID‐19 lockdown in LanzhouThe reduction of aerosol was mainly due to a decline in secondary species; we identify an overall low production rate as the main driverThe result is contrast to those reported recently in East China where the reductions were offset by an increase in secondary species production [ABSTRACT FROM AUTHOR]

Emission datasets of nitrogen oxides (NOx) at high horizontal resolutions (e.g., 0.05∘×0.05∘) are crucial for understanding human influences at fine scales, air quality studies, and pollution control. Yet high-resolution emission data are often missing or contain large uncertainties especially for the developing regions. Taking advantage of long-term satellite measurements of nitrogen dioxide (NO2), here we develop a computationally efficient method of estimating NOx emissions in major urban areas at the 0.05∘×0.05∘ resolution. The top-down inversion method accounts for the nonlinear effects of horizontal transport, chemical loss, and deposition. We construct a two-dimensional Peking University High-resolution Lifetime-Emission-Transport model (PHLET), its adjoint model (PHLET-A), and a satellite conversion matrix approach to relate emissions, lifetimes, simulated NO2 , and satellite NO2 data. The inversion method is applied to the summer months of 2012–2015 in the Yangtze River Delta (YRD; 29–34 ∘ N, 118–123 ∘ E) area, a major polluted region of China, using the NO2 vertical column density data from the Peking University Ozone Monitoring Instrument NO2 product (POMINO). A systematic analysis of inversion errors is performed, including using an independent test based on GEOS-Chem simulations. Across the YRD area, the summer average emissions obtained in this work range from 0 to 15.3 kg km -2 h -1 , and the lifetimes (due to chemical loss and deposition) range from 0.6 to 3.3 h. Our emission dataset reveals fine-scale spatial information related to nighttime light, population density, road network, maritime shipping, and land use (from a Google Earth photo). We further compare our emissions with multiple inventories. Many of the fine-scale emission structures are not well represented or not included in the widely used Multi-scale Emissions Inventory of China (MEIC). [ABSTRACT FROM AUTHOR]

Gas flaring is a commonly used practice in the oil and gas sector that leads to key air pollutant and greenhouse gas emissions. Here we use multipollutant (NO2, SO2) satellite observations from 2005 to 2017 to quantify gas flaring activity in Mexico's offshore production cluster, which produces ~50–70% of the country's oil and is among the world's largest oil fields. We estimate annual flared gas volume ranging from 5.5 to 20 × 109 m3 over the Mexican offshore corresponding to >40% associated gas production, which is significantly larger than for instance offshore United States where reportedly <3% of associated gas is flared. The 13‐year record of satellite‐derived gas flaring indicates a drastic increase until 2008 and a decline afterward. While the increased flaring is associated with efforts to enhance oil production, the post‐2008 decline is linked to an expanding capacity of associated gas utilization, providing a continuing opportunity to reduce flaring for environmental and economic benefits. Plain Language Summary: Gas flaring, a commonly used practice in the oil and gas sector to burn off associated natural gas, leads to significant economic loss and emissions of key air pollutants (e.g., SO2 and NO2) and greenhouse gases (e.g., methane and carbon dioxide). Global efforts have been underway to reduce gas flaring, which is considered a viable mitigation option to reduce criteria air pollutants and greenhouse gas emissions, because of technology availability and potential economic gains. In this context, it becomes increasingly important to independently quantify and track gas flaring activity over time, as well as independently evaluate progress in oil/gas regulations and policy implementation, toward mitigation measures. Here we applied a combined analysis of satellite NO2 and SO2 observations over offshore Mexico, one of the world's largest offshore oil production complexes, during 2005–2017. The 13‐year record showed an increase in gas flaring until 2008 associated with efforts to enhance oil production and a decline after 2008 linked to an expanding capacity of associated gas utilization. Key Points: A combined analysis of satellite NO2 and SO2 observations is useful for quantifying and tracking gas flaring activities over timeSatellite‐derived flared gas volume well captures the interannual variability of the reported flaring activity in offshore MexicoGas flaring activity in offshore Mexico peaked in 2008 and declined steadily after 2008, reflecting progress in policy implementation [ABSTRACT FROM AUTHOR]

With the improved spatial resolution of the Ozone Monitoring Instrument (OMI) over earlier instruments and more than 10 years of service, tropospheric NO2 retrievals from OMI have led to many influential studies on the relationships between socioeconomic activities and NOx emissions. Previous studies have shown that the OMI NO2 data show different relative trends compared to in situ measurements. However, the sources of the discrepancies need further investigations. This study focuses on how to appropriately compare relative trends derived from OMI and in situ measurements. We retrieve OMI tropospheric NO2 vertical column densities (VCDs) and obtain the NO2 seasonal trends over the United States, which are compared with coincident in situ surface NO2 measurements from the Air Quality System (AQS) network. The Mann-Kendall method with Sen's slope estimator is applied to derive the NO2 seasonal and annual trends for four regions at coincident sites during 2005-2014. The OMI-based NO2 seasonal relative decreasing trends are generally biased low compared to the in situ trends by up to 3.7%yr-1, except for the underestimation in the US Midwest and Northeast during December, January, and February (DJF). We improve the OMI retrievals for trend analysis by removing the ocean trend, using the Moderate Resolution Imaging Spectroradiometer (MODIS) albedo data in air mass factor (AMF) calculation. We apply a lightning flash filter to exclude lightning-affected data to make proper comparisons. These data processing procedures result in close agreement (within 0.3%yr-1) between in situ and OMI-based NO2 regional annual relative trends. The remaining discrepancies may result from inherent difference between trends of NO2 tropospheric VCDs and surface concentrations, different spatial sampling of the measurements, chemical nonlinearity, and tropospheric NO2 profile changes. We recommend that future studies apply these procedures (ocean trend removal and MODIS albedo update) to ensure the quality of satellite-based NO2 trend analysis and apply the lightning filter in studying surface NOx emission changes using satellite observations and in comparison with the trends derived from in situ NO2 measurements. With these data processing procedures, we derive OMI-based NO2 regional annual relative trends using all available data for the US West (-2.0%±0.3 yr-1), Midwest (-1.8%±0.4 yr-1), Northeast (-3.1%±0.5 yr-1), and South (-0.9%±0.3 yr-1). The OMI-based annual mean trend over the contiguous United States is -1.5%±0.2 yr-1. It is a factor of 2 lower than that of the AQS in situ data (-3.9%±0.4 yr-1); the difference is mainly due to the fact that the locations of AQS sites are concentrated in urban and suburban regions. [ABSTRACT FROM AUTHOR]

Recent studies have revealed a significant influx of anthropogenic aerosol from South Asia to the Himalayas and Tibetan Plateau (TP) during pre-monsoon period. In order to characterize the chemical composition, sources, and transport processes of aerosol in this area, we carried out a field study during June 2015 by deploying a suite of online instruments including an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-AMS) and a multi-angle absorption photometer (MAAP) at Nam Co station (90°57' E, 30°46' N; 4730ma.s.l.) at the central of the TP. The measurements were made at a period when the transition from premonsoon to monsoon occurred. The average ambient mass concentration of submicron particulate matter (PM1/ over the whole campaign was ~2.0 μgm-3, with organics accounting for 68 %, followed by sulfate (15 %), black carbon (8 %), ammonium (7 %), and nitrate (2 %). Relatively higher aerosol mass concentration episodes were observed during the pre-monsoon period, whereas persistently low aerosol concentrations were observed during the monsoon period. However, the chemical composition of aerosol during the higher aerosol concentration episodes in the pre-monsoon season was on a case-by-case basis, depending on the prevailing meteorological conditions and air mass transport routes. Most of the chemical species exhibited significant diurnal variations with higher values occurring during afternoon and lower values during early morning, whereas nitrate peaked during early morning in association with higher relative humidity and lower air temperature. Organic aerosol (OA), with an oxygen-to-carbon ratio (O / C) of 0.94, was more oxidized during the pre-monsoon period than during monsoon (average O/C ratio of 0.72), and an average O/C was 0.88 over the entire campaign period, suggesting overall highly oxygenated aerosol in the central TP. Positive matrix factorization of the high-resolution mass spectra of OA identified two oxygenated organic aerosol (OOA) factors: a less oxidized OOA (LO-OOA) and a more oxidized OOA (MO-OOA). The MO-OOA dominated during the pre-monsoon period, whereas LO-OOA dominated during monsoon. The sensitivity of air mass transport during pre-monsoon with synoptic process was also evaluated with a 3-D chemical transport model. [ABSTRACT FROM AUTHOR]

Since its first confirmed case at the end of 2019, COVID-19 has become a global pandemic in three months with more than 1.4 million confirmed cases worldwide, as of early April 2020. Quantifying the changes of pollutant emissions due to COVID-19 and associated governmental control measures is crucial to understand its impacts on economy, air pollution, and society. We used the WRF-GC model and the tropospheric NO2 column observations retrieved by the TROPOMI instrument to derive the top-down NOx emission change estimation between the three periods: P1 (January 1st to January 22nd, 2020), P2 (January 23rd, Wuhan lockdown, to February 9th, 2020), and P3 (February 10th, back-to-work day, to March 12th, 2020). We found that NOx emissions in East China averaged during P2 decreased by 50% compared to those averaged during P1. The NOx emissions averaged during P3 increased by 26% compared to those during P2. Most provinces in East China gradually regained some of their NOx emissions after February 10, the official back-to-work day, but NOx emissions in most provinces have not yet to return to their previous levels in early January. NOx emissions in Wuhan, the first epicenter of COVID-19, had no sign of emission recovering by March 12. A few provinces, such as Zhejiang and Shanxi, have recovered fast, with their averaged NOx emissions during P3 almost back to pre-lockdown levels. [ABSTRACT FROM AUTHOR]

Nitrogen oxides (NO x =NO+NO 2 ) play a crucial role in the formation of ozone and secondary inorganic and organic aerosols, thus affecting human health, global radiation budget, and climate. The diurnal and spatial variations in NO 2 are functions of emissions, advection, deposition, vertical mixing, and chemistry. Their observations, therefore, provide useful constraints in our understanding of these factors. We employ a Regional chEmical and trAnsport model (REAM) to analyze the observed temporal (diurnal cycles) and spatial distributions of NO 2 concentrations and tropospheric vertical column densities (TVCDs) using aircraft in situ measurements and surface EPA Air Quality System (AQS) observations as well as the measurements of TVCDs by satellite instruments (OMI: the Ozone Monitoring Instrument; GOME-2A: Global Ozone Monitoring Experiment - 2A), ground-based Pandora, and the Airborne Compact Atmospheric Mapper (ACAM) instrument in July 2011 during the DISCOVER-AQ campaign over the Baltimore-Washington region. The model simulations at 36 and 4 km resolutions are in reasonably good agreement with the regional mean temporospatial NO 2 observations in the daytime. However, we find significant overestimations (underestimations) of model-simulated NO 2 (O 3 ) surface concentrations during night-time, which can be mitigated by enhancing nocturnal vertical mixing in the model. Another discrepancy is that Pandora-measured NO 2 TVCDs show much less variation in the late afternoon than simulated in the model. The higher-resolution 4 km simulations tend to show larger biases compared to the observations due largely to the larger spatial variations in NO x emissions in the model when the model spatial resolution is increased from 36 to 4 km. OMI, GOME-2A, and the high-resolution aircraft ACAM observations show a more dispersed distribution of NO 2 vertical column densities (VCDs) and lower VCDs in urban regions than corresponding 36 and 4 km model simulations, likely reflecting the spatial distribution bias of NO x emissions in the National Emissions Inventory (NEI) 2011., Competing Interests: Competing interests. The authors declare that they have no conflict of interest.

Using new satellite observations and atmospheric inverse modeling, we report methane emissions from the Permian Basin, which is among the world's most prolific oil-producing regions and accounts for >30% of total U.S. oil production. Based on satellite measurements from May 2018 to March 2019, Permian methane emissions from oil and natural gas production are estimated to be 2.7 ± 0.5 Tg a -1 , representing the largest methane flux ever reported from a U.S. oil/gas-producing region and are more than two times higher than bottom-up inventory-based estimates. This magnitude of emissions is 3.7% of the gross gas extracted in the Permian, i.e., ~60% higher than the national average leakage rate. The high methane leakage rate is likely contributed by extensive venting and flaring, resulting from insufficient infrastructure to process and transport natural gas. This work demonstrates a high-resolution satellite data-based atmospheric inversion framework, providing a robust top-down analytical tool for quantifying and evaluating subregional methane emissions., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)