Angle-Only Cooperative Orbit Determination Considering Attitude Uncertainty.

In this paper, a novel concept for cooperative orbit determination (OD) using inter-spacecraft angle-only measurements is proposed. Different from the conventional cooperative OD that only estimates orbit states, the attitude of the observer spacecraft is considered by incorporating the attitude into the estimated vector. The observability of a two-spacecraft system is analyzed based on the observability matrix. Observability analysis reveals that inter-spacecraft angle-only measurements are inadequate to estimate both the attitude and the orbit states in two-body dynamics. The observability of the two-spacecraft system can be improved by considering high-order gravitational perturbation or executing an attitude maneuver on the observer spacecraft. This is the first time that we present the observability analysis and orbit estimation results for a two-spacecraft system considering attitude uncertainty for the observer. Finally, simulation results demonstrate the effectiveness of the proposed method. The results in this paper can be potentially useful for autonomous managements of a spacecraft constellation and formation.

Visibility, aerosol optical depth, and low-visibility events in Bangkok during the dry season and associated local weather and synoptic patterns.

Visibility and aerosol optical depth (AOD) characterization, and their relationship with PM10 and local and synoptic meteorology, were studied for January-March in 2014 and 2015 over Bangkok. Visibility degradation intensifies in the dry season as compared to the wet season due to increase in PM10 and unfavorable meteorological conditions. The average visibility is lower in January and February as compared to the other months. Relatively higher AOD in March despite lower PM10 is attributed to the synergetic effect of moderate relative humidity, secondary aerosols, elevated aerosol layer due to summertime convection, and biomass burning. Larger variability in visibility and PM10 in winter months is due to more synoptic weather fluctuations while AOD shows similar variability for all months attributed partly to fires. Higher PM10 and moderate-to-high relative humidity cause lower visibility in the morning while it improves in afternoon as PM10 and relative humidity decrease. AOD is higher in the afternoon as compared to that in the morning and evening as it is less sensitive to diurnal change in aerosols and meteorology at the surface level. Visibility and AOD relationships with PM10 are dependent on relative humidity. Weaker winds lead to lower visibility, higher PM10, and higher AOD irrespective of wind direction. Stronger winds improve visibility and decrease PM10 for all directions while AOD is higher for all directions except eastern and northeastern. The back-trajectory results show that the transport of pollutant and moist air is coupled with the synoptic weather and influence visibility and AOD. Two low-visibility events were investigated. The first event is potentially caused by the combined effect of local emissions and their accumulation due to stagnant weather conditions, secondary aerosols, and forest fires in the nearby regions. The second event can be attributed to the local emission and fires in the nearby area with hygroscopic growth of aerosols due to moist air from the Gulf of Thailand. Based on these findings, some policy implications have also been given.

Recent Advances on the Model, Measurement Technique, and Application of Single Cell Mechanics.

Since the cell was discovered by humans, it has been an important research subject for researchers. The mechanical response of cells to external stimuli and the biomechanical response inside cells are of great significance for maintaining the life activities of cells. These biomechanical behaviors have wide applications in the fields of disease research and micromanipulation. In order to study the mechanical behavior of single cells, various cell mechanics models have been proposed. In addition, the measurement technologies of single cells have been greatly developed. These models, combined with experimental techniques, can effectively explain the biomechanical behavior and reaction mechanism of cells. In this review, we first introduce the basic concept and biomechanical background of cells, then summarize the research progress of internal force models and experimental techniques in the field of cell mechanics and discuss the latest mechanical models and experimental methods. We summarize the application directions of cell mechanics and put forward the future perspectives of a cell mechanics model.

An Integrated Source Apportionment Methodology and Its Application over the Yangtze River Delta Region, China.

An integrated source apportionment methodology is developed by amalgamating the receptor-oriented model (ROM) and source-oriented numerical simulations (SOM) together to eliminate the weaknesses of individual SA methods. This approach attempts to apportion and dissect the PM2.5 sources in the Yangtze River Delta region during winter. First, three ROM models (CMB, PMF, ME2) are applied and compared for the preliminary SA results, with information from PM2.5 sampling and lab analysis during the winter seasons. The detailed source category contribution of SOM to PM2.5 is further simulated using the WRF-CAMx model. The two pieces of information from both ROM and SOM are then stitched together to give a comprehensive information on the PM2.5 sources over the region. With the integrated approach, the detailed contributing sources of the ambient PM2.5 at different receptors including rural and urban, coastal and in-land, northern and southern receptors are analyzed. The results are compared with previous data and shows good agreement. This integrative approach is more comprehensive and is able to produce a more profound and detailed understanding between the sources and receptors, compared with single models.

Evaluation of one-dimensional and two-dimensional volatility basis sets in simulating the aging of secondary organic aerosol with smog-chamber experiments.

We evaluate the one-dimensional volatility basis set (1D-VBS) and two-dimensional volatility basis set (2D-VBS) in simulating the aging of SOA derived from toluene and α-pinene against smog-chamber experiments. If we simulate the first-generation products with empirical chamber fits and the subsequent aging chemistry with a 1D-VBS or a 2D-VBS, the models mostly overestimate the SOA concentrations in the toluene oxidation experiments. This is because the empirical chamber fits include both first-generation oxidation and aging; simulating aging in addition to this results in double counting of the initial aging effects. If the first-generation oxidation is treated explicitly, the base-case 2D-VBS underestimates the SOA concentrations and O:C increase of the toluene oxidation experiments; it generally underestimates the SOA concentrations and overestimates the O:C increase of the α-pinene experiments. With the first-generation oxidation treated explicitly, we could modify the 2D-VBS configuration individually for toluene and α-pinene to achieve good model-measurement agreement. However, we are unable to simulate the oxidation of both toluene and α-pinene with the same 2D-VBS configuration. We suggest that future models should implement parallel layers for anthropogenic (aromatic) and biogenic precursors, and that more modeling studies and laboratory research be done to optimize the "best-guess" parameters for each layer.

Investigation into the nocturnal ozone in a typical industrial city in North China Plain, China.

Ozone (O3) concentrations usually peak at midday by photochemical reactions and gradually decline after sunset due to chemical destruction and dry deposition. However, an increase in the frequency of elevated nocturnal ozone enhancement (NOE) and high nocturnal ozone value (HNOV) has been frequently observed in urban areas of eastern China, but the reasons are not well understood. In this study, taking a typical industrial city, ZiBo as a case study, we analyzed the trends, characteristics, and causes of the NOE and HNOV events in historical years by combining observations and model simulations. During the warm season (April-September) of 2017-2023, HNOV events are accompanied by low humidity, high temperature, large friction velocity, and a high boundary layer (52 days in total), whereas NOE events coincide with increases in humidity, wind speed, friction velocity, and boundary layer height (141 days in total). During the HNOV and NOE events, the nighttime average concentrations of Ox were 77 ± 7 and 12 ± 6 µg m-3 higher than the non-nocturnal O3 period, indicating enhanced atmospheric oxidizing capacity during nighttime. The modeling results indicate that both the HNOV and NOE events were mainly driven by vertical mixing and regional transport. We selected a typical period with high O3 pollution and frequent NOE and HNOV events to conduct the modeling study. Three typical nocturnal O3 events are identified: Case I was mainly driven by horizontal transport; while in the two subsequent cases, the vertical transport contribution was 80 µg m-3 h-1 (20:00 LT on June 21, 2021) and 35 µg m-3 h-1 (02:00 LT on June 26, 2021), respectively. Our study reveals that the O3 pollution in industrial cities has been extending to nighttime, primarily attributed to vertical mixing and horizontal transport within the boundary layer. This highlights the critical role of implementing regional joint control action to reduce primary emissions and eliminate residual ozone.

Study of condensable particulate matter from stationary combustion sources: Source profiles, emissions, and impact on ambient fine particulate matter.

Although significant progress has been made in controlling emissions from stationary combustion sources in China over the past decade, understanding of condensable particulate matter (CPM) emissions from these sources and their impact on ambient PM2.5 remains limited. In this study, we established the source profiles and emission inventories of CPM from coal-fired industrial boilers (CFIBs), coal-fired power plants (CFPPs), and iron and steel industry (ISIs) for the Yangtze River Delta (YRD) region of China; furthermore, the air quality model (Community Multiscale Air Quality, CMAQ) was used to evaluate the impact of CPM emissions from these three types of stationary combustion sources on ambient PM2.5 during Feb. 2018, a month characterized by elevated PM2.5 concentrations. The results indicated that CPM emissions from these three sources in the YRD region before and after the implementation of the ultra-low emissions (ULE) policy amounted to 109,839 and 43,338 tons, respectively, with particularly high emission intensity along the Yangtze River. The implementation of CFPPs ULE policy was shown to reduce the impact of CPM emissions from these three stationary sources on monthly PM2.5 concentrations from 0.92 µg/m3 to 0.41 µg/m3 (with a maximum of 5.35 µg/m3). This reduction exceeded the 0.31 µg/m3 decrease in PM2.5 concentrations resulting from the emission reductions of conventional pollutants (FPM, SO2 and NOx). CPM emissions from these three stationary sources were found to increase the PM2.5 by 0.68 µg/m3 during pollution periods. The largest components of PM2.5 contributed by CPM emissions from stationary combustion sources were sulfate, organic carbon, and nitrate, accounting for 21.4 %, 21.1 %, and 18.2 %, respectively. Particularly, contributions from CPM emissions to PM2.5 varied by altitude, with a relatively large impact at altitudes between 220 and 460 m. Attention should be given to CPM emission control, with particular priority placed on implementing ULE measures for ISIs and CFIBs.

Long-term changes of methane emissions from rice cultivation during 2000 - 2060 in China: Trends, driving factors, predictions and policy implications.

Regional budget assessments of methane (CH4) are critical for future climate and environmental management. CH4 emissions from rice cultivation (CH4-rice) constitute one of the most significant sources. However, previous studies mainly focus on historical emission estimates and lack consideration of future changes in CH4-rice under climate change or anthropogenic policy intervention, which hampers our understanding of long-term trends and the implementation of targeted emission reduction efforts. This study investigates the spatiotemporal variations of CH4-rice over the past two decades, using an integrated method to identify the major drivers and predict future emissions under climate change scenarios and policy perspectives. Results indicate that the CH4-rice emissions in China ranged between 6.21 and 6.57 Tg yr-1 over the past two decades, with a spatial distribution characterized by decreases in the south and increases in the north, associated with economic development, dietary shifts, technological advancements, and climate change. Factors such as the rate of straw added (RSA), fertilization, soil texture, temperature, and precipitation significantly influence CH4 emissions per unit rice production (CH4-urp), with RSA identified as the most significant tillage management factor, explaining 32 % of the variance. Lowering RSA to 8 % is beneficial for reducing CH4-urp. Scenario analysis indicates that under policies focusing on production or demand, CH4-rice is expected to increase by 0.3 % to 5.6 %, while adjusting RSA can reduce CH4-rice by 9.4 % to 10.0 %. Structural adjustments and regional cooperation serve as beneficial starting points for controlling and reducing CH4-rice in China, while optimizing industrial layouts contributes to regional development and CH4-rice control. Implementing policies related to maintaining field and crop yields can achieve a balance between rice supply and demand ahead of schedule. Dynamic adjustment of rice cultivation based on supply-demand balance can effectively reduce CH4-rice from excess rice production. By 2060, the reduction effect could reach 8.95 %-12.01 %. Introducing policy-driven tillage management measures as reference indicators facilitates the reduction of CH4-rice.

Regional background ozone estimation for China through data fusion of observation and simulation.

Regional background ozone (O3_RBG) is an important component of surface ozone (O3). However, due to the uncertainties in commonly used Chemical Transport Models (CTMs) and statistical models, accurately assessing O3_RBG in China is challenging. In this study, we calculated the O3_RBG concentrations with the CTM - Brute Force Method (BFM) and constrained the results with site observations of O3 with the multiple linear regression (MLR) model. The annual average O3_RBG concentration in China region in 2020 is 35 ± 4 ppb, accounting for 81 ± 5 % of the maximum 8-h average O3 (MDA8 O3). We applied the random forest and Shapley additive explanations based on meteorological standardization techniques to separate the contributions of meteorology and natural emissions to O3_RBG. Natural emissions contribute more significantly to O3_RBG than meteorology in various Chineses regions (30-40 ppb), with higher contributions during the warm season. Meteorological factors show higher contributions in the spring and summer seasons (2-3 ppb) than the other seasons. Temperature and humidity are the primary contributors to O3_RBG in regions with severe O3 pollution in China, with their individual impacts ranging from 30 % to 62 % of the total impacts of all meteorological factors in different seasons. For policy implications, we tracked the contributions of O3_RBG and local photochemical reaction contributions (O3_LC) to total O3 concentration at different O3 levels. We found that O3_LC contribute over 45 % to MDA8 O3 on polluted days, supporting the current Chinese policy of reducing O3 peak concentrations by cutting down precursor emissions. However, as the contribution of O3_RBG is not considered in the policy, additional efforts are needed to achieve the control groal of O3 concentration. As the implementation of stringent O3 control measurements in China, the contribution of O3_RBG become increasingly significant, suggesting the need for attention to O3_RBG and regional joint prevention and control.

Estimating visibility and understanding factors influencing its variations at Bangkok airport using machine learning and a game theory-based approach.

In this study, six individual machine learning (ML) models and a stacked ensemble model (SEM) were used for daytime visibility estimation at Bangkok airport during the dry season (November-April) for 2017-2022. The individual ML models are random forest, adaptive boosting, gradient boosting, extreme gradient boosting, light gradient boosting machine, and cat boosting. The SEM was developed by the combination of outputs from the individual models. Furthermore, the impact of factors affecting visibility was examined using the Shapley Additive exPlanation (SHAP) method, an interpretable ML technique inspired by the game theory-based approach. The predictor variables include different air pollutants, meteorological variables, and time-related variables. The light gradient boosting machine model is identified as the most effective individual ML model. On an hourly time scale, it showed the best performance across three out of four metrics with the ρ = 0.86, MB = 0, ME = 0.48 km (second lowest), and RMSE = 0.8 km. On a daily time scale, the model performed the best for all evaluation metrics with ρ = 0.92, MB = 0.0 km, ME = 0.3 km, and RMSE = 0.43 km. The SEM outperformed all the individual models across three out of four metrics on an hourly time scale with ρ = 0.88, MB = 0.0 km, (second lowest), and RMSE = 0.75 km. On the daily scale, it performed the best with ρ = 0.93, MB = 0.02 km, ME = 0.27 km, and RMSE = 0.4 km. The seasonal average original (VISorig) and meteorologically normalized visibility (VISnorm) decrease from 2017 to 2021 but increase in 2022. The rate of decrease in VISorig is double than rate of decrease in VISnorm which suggests the effect of meteorology visibility degradation. The SHAP analysis identified relative humidity (RH), PM2.5, PM10, day of the season year (i.e., Julian day) (JD), and O3 as the most important variables affecting visibility. At low RH, visibility is not sensitive to changes in RH. However, beyond a threshold, a negative correlation between RH and visibility is found potentially due to the hygroscopic growth of aerosols. The dependence of the Shapley values of PM2.5 and PM10 on RH and the change in average visibilities under different RH intervals also suggest the effect of hygroscopic growth of aerosol on visibility. A negative relationship has been identified between visibility and both PM2.5 and PM10. Visibility is positively correlated with O3 at lower to moderate concentrations, with diminishing impact at very high concentrations. The JD is strongly negatively related to visibility during winter while weakly associated positively later in summer. Findings from this research suggest the feasibility of employing machine learning techniques for predicting visibility and understanding the factors influencing its fluctuations.

Experiment investigation on effects of elastic modulus on cavitation erosion of silicone rubber.

Research into cavitation phenomena in various fields shows that the elastic modulus of a boundary has a potential impact on cavitation erosion. To obtain the direct relationship between the elastic modulus of the boundary and cavitiation erosion, single-layer samples with different chemical composition and moduli, and double-layer samples with different elastic moduli and the same surface layer material, were prepared with silicone rubber. The results of cavitation experiments on single-layer samples, show that the coating chemical composition and mechanical properties together affect the cavitation morphology of the coating, and dominant factors vary with erosion stage. Through the cavitation test of double-layer samples, it was found that there is a positive correlation between the elastic modulus of the coating and the degree of cavitation. This study helps us to understand the relationship between coating elastic modulus and cavitation more directly, and provides theoretical and technical guidance for the application of anti-cavitation for elastic coating in engineering.

Modeling of secondary organic aerosols (SOA) based on two commonly used air quality models in China: Consistent S/IVOCs contribution but large differences in SOA aging.

Secondary organic aerosol (SOA) is an important component of atmospheric fine particulate matter (PM2.5), with contributions from anthropogenic and biogenic volatile organic compounds (AVOC and BVOC) and semi- (SVOC) and intermediate volatility organic compounds (IVOC). Policymakers need to know which SOA precursors are important but accurate simulation of SOA magnitude and contributions remain uncertain. Findings from existing SOA modeling studies have many inconsistencies due to differing emission inventory methodologies/assumptions, air quality model (AQM) algorithms, and other aspects of study methodologies. To address some of the inconsistencies, we investigated the role of different AQM SOA algorithms by applying two commonly used models, CAMx and CMAQ, with consistent emission inventories to simulate SOA concentrations and contributions for July and November 2018 in China. Both models have a volatility basis set (VBS) SOA algorithm but with different parameters and treatments of SOA photochemical aging. SOA generated from BVOC (i.e., BSOA) is found to be more important in southern China. In contrast, SOA generated from anthropogenic precursors is more prevalent in the North China Plain (NCP), Yangtze River Delta (YRD), Sichuan Basin and Central China. Both models indicate negligible SOA formation from SVOC emissions compared to other precursors. In July, when BVOC emissions are abundant, SOA is predominantly contributed by BSOA (except for NCP), followed by IVOC-SOA (i.e., SOA produced from IVOC) and ASOA (i.e., SOA produced from anthropogenic VOC). In contrast, in November, IVOC became the leading SOA contributor for all selected regions except PRD, illustrating the important contribution of IVOC emissions to SOA formation. While both models generally agree in terms of the spatial distributions and seasonal variations of different SOA components, CMAQ tends to predict higher BSOA, while CAMx generates higher ASOA concentrations. As a result, CMAQ results suggest that BSOA concentration is always higher than ASOA in November, while CAMx emphasizes the importance of ASOA. Utilizing a conceptual model, we found that different treatment of SOA aging between the two models is a major cause of differences in simulated ASOA concentrations. The step-wise SOA aging scheme implemented in the CAMx VBS (based on gas-phase reactions with OH radical and similar to other models) exhibits a strong enhancement effect on simulated ASOA concentrations, and this effect increases with the ambient organic aerosol (OA) concentrations. The CMAQ aerosol module implements a different SOA aging scheme that represents particle-phase oligomerization and has smaller impacts on total OA. Different structures and/or parameters of the SOA aging schemes are being used in current models, which could greatly affect model simulations of OA in ways that are difficult to anticipate. Our results indicate that future control policies should aim at reducing IVOC emissions as well as traditional VOC emissions. In addition, aging schemes are the major driver in CMAQ vs. CAMx treatments of ASOA and their resulting predicted mass. More sophisticated measurement data (e.g., with resolved OA components) and/or chamber experiments (e.g., investigating how aging influences SOA yields) are needed to better characterize SOA aging and constrain model parameterizations.

Assessing the contribution of open crop straw burning to ground-level ozone and associated health impacts in China and the effectiveness of straw burning bans.

In recent years, ozone pollution in China has been shown to increase in frequency and persistence despite the concentrations of fine particulate matter (PM2.5) decreasing steadily. Open crop straw burning (OCSB) activities are extensive in China and emit large amounts of trace gases during a short period that could lead to elevated ozone concentrations. This study addresses the impacts of OCSB emissions on ground-level ozone concentration and the associated health impact in China. Total VOCs and NOx emissions from OCSB in 2018 were 798.8 Gg and 80.6 Gg, respectively, with high emissions in Northeast China (31.7%) and North China (23.7%). Based on simulations conducted for 2018, OCSB emissions are estimated to contribute up to 0.95 µg/m3 increase in annual averaged maximum daily 8-hour (MDA8) ozone and up to 1.35 µg/m3 for the ozone season average. The significant impact of OCSB emissions on ozone is mainly characterized by localized and episodic (e.g., daily) changes in ozone concentration, up to 20 µg/m3 in North China and Yangtze River Delta region and even more in Northeast China during the burning season. With the implementation of straw burning bans, VOCs and NOx emissions from OCSB dropped substantially by 46.9%, particularly over YRD (76%) and North China (60%). Consequently, reduced OCSB emissions result in an overall decrease in annual averaged MDA8 ozone, and reductions in monthly MDA8 ozone could be over 10 µg/m3 in North China. The number of avoided premature death due to reduced OCSB emissions (considering both PM2.5 and ozone) is estimated to be 6120 (95% Confidence Interval: 5320-6800), with most health benefits gained over east and central China. Our results illustrate the effectiveness of straw burning bans in reducing ozone concentrations at annual and national scales and the substantial ozone impacts from OCSB events at localized and episodic scales.

[Source Analysis of Ozone and Its Precursors in Zibo Based on 3-D Air Quality Model].

Based on the ISAM module in the WRF-CMAQ model, this study analyzed the source contribution(both regional and sectoral) of O3 and its precursors(NO2 and VOCs) in Zibo in June 2021. Days with a maximum daily 8-h average(MDA8) O3 higher(lower) than 160 µg·m-3 were defined as polluted(clean) days. Differences in the source contribution between clean days and polluted days were compared, and a typical pollution period was selected for further process analysis. The results showed that NO2 in Zibo mainly came from local emissions in summer, with a relative contribution of 45.1%. Vehicle emissions(33.8%) and natural sources(20.7%) were the primary NO2 sources. VOC contributions from natural sources, solvent usage, and the petrochemical industry were significant, with a total contribution of 78.5%. The MDA8 contribution from local sources was 21.4%, whereas the impact of regional transport(32%) and surrounding cities(26.8%) was also substantial. Among local emission sources, vehicle emissions, the power industry, and the building materials industry contributed 10.9%-18.8% to local MDA8. On O3 pollution days, the MDA8 contribution from local emissions and surrounding cities increased. However, the relative contributions from local sources were similar under different pollution conditions.

Developed compositional source profile and estimated emissions of condensable particulate matter from coal-fired power plants: A case study of Yantai, China.

The emission and environmental impact of condensable particulate matter (CPM) from coal-fired power plants (CFPPs) are of increasing concern worldwide. Many studies on the characteristics of CPM emission have been conducted in China, but its source profile remains unclear, and its emission inventory remains high uncertainty. In this work, the latest measurements reported in the latest 33 studies for CPM inorganic and organic species emitted from CFPPs in China were summarized, and then a compositional source profile of CPM for CFPPs was developed for the first time in China, which involved 10 inorganic species and 71 organic species. In addition, the CPM emission inventory of CFPPs in Yantai of China was developed based on surveyed activity data, continuous emission monitoring system (CEMS), and the latest measurement data. The results show that: (1) Inorganic species accounted for 77.64 % of CPM emitted from CFPPs in Yantai, among which SO42- had the highest content, accounting for 23.74 % of CPM, followed by Cl-, accounting for 11.95 %; (2) Organic matter accounted for 22.36 % of CPM, among which alkanes accounted for the largest proportion of organic fraction (72.7 %); (3) Emission concentration method (EC) and CEMS-based emission ratio method (ERFPM,CEMS) were recommended to estimate CPM emissions for CFPPs; (4) The estimated CPM emission inventories of Yantai CFPPs in 2020 by the EC method and the ERFPM,CEMS method were 1231 tons and 929 tons, respectively, with uncertainties of -34 % ∼ 33 % and -27 % ∼ 57 %, respectively; (5) CPM emissions were mainly distributed in the northern coastal areas of Yantai. This developed CPM source profile and emission inventory can provide basic data for assessing the impacts of CPM on air quality and health. In addition, this study can provide an important methodology for developing CPM emission inventories and CPM emission source profiles for stationary combustion sources in other regions.

Differences between VOCs and NOx transport contributions, their impacts on O3, and implications for O3 pollution mitigation based on CMAQ simulation over the Yangtze River Delta, China.

The relationship between O3 and its precursors during urban polluted episodes remains unclear. In this study, the simultaneous source apportionment of VOCs, NOx, and O3 over the Yangtze River Delta (YRD) region during the O3 polluted episode on July 24-30, 2018, was performed based on the Integrated Source Apportionment Method (ISAM) embedded in the Community Multiscale Air Quality Modeling System (CMAQ). The results of the ISAM were compared with those of the Brute Force Method (BFM) and Positive Matrix Factorization (PMF). Furthermore, the differences between the transport contributions of VOCs and NOx, and their impacts on O3 were analyzed. The results indicate that observations of VOCs species can be well captured by simulated VOCs, and the ISAM has a significant advantage in the source apportionment of VOCs, especially for sources emitting highly reactive species. In the clean and polluted periods, the local contribution percentages of VOCs in urban sites ranged from 60 % to 77 %, much higher than those of NOx (31 %-43 %) and O3 (16 %-33 %). NOx and O3 have strong transport abilities with high and close contribution percentages, which are highly correlated, mainly because oxygen atoms produced by the photolysis of NO2 in the aged air mass combined rapidly with O2 to form O3 during transport. The VOCs chemical loss caused by the oxidation of OH radicals during transport makes the ability of VOCs for long-distance transport much weaker than that of NOx. Furthermore, owing to the sufficient aging of VOCs, those contributed by long-distance transport have little effect on O3. To a certain extent, controlling one's NOx emissions can help other cities more, while controlling one's VOCs emissions can help itself more. Therefore, it is recommended to attach enough importance to joint prevention and control of NOx among cities and even long-distance areas to alleviate regional O3 pollution.

Underestimation of biomass burning contribution to PM2.5 due to its chemical degradation based on hourly measurements of organic tracers: A case study in the Yangtze River Delta (YRD) region, China.

Biomass burning (BB) has significant impacts on air quality and climate change, especially during harvest seasons. In previous studies, levoglucosan was frequently used for the calculation of BB contribution to PM2.5, however, the degradation of levoglucosan (Lev) could lead to large uncertainties. To quantify the influence of the degradation of Lev on the contribution of BB to PM2.5, PM2.5-bound biomass burning-derived markers were measured in Changzhou from November 2020 to March 2021 using the thermal desorption aerosol gas chromatography-mass spectrometry (TAG-GC/MS) system. Temporal variations of three anhydro-sugar BB tracers (e.g., levoglucosan, mannosan (Man), and galactosan (Gal)) were obtained. During the sampling period, the degradation level of air mass (x) was 0.13, indicating that ~87 % of levoglucosan had degraded before sampling in Changzhou. Without considering the degradation of levoglucosan in the atmosphere, the contribution of BB to OC were 7.8 %, 10.2 %, and 9.3 % in the clean period, BB period, and whole period, respectively, which were 2.4-2.6 times lower than those (20.8 %-25.9 %) considered levoglucosan degradation. This illustrated that the relative contribution of BB to OC could be underestimated (~14.9 %) without considering degradation of levoglucosan. Compared to the traditional method (i.e., only using K+ as BB tracer), organic tracers (Lev, Man, Gal) were put into the Positive Matrix Factorization (PMF) model in this study. With the addition of BB organic tracers and replaced K+ with K+BB (the water-soluble potassium produced by biomass burning), the overall contribution of BB to PM2.5 was enhanced by 3.2 % after accounting for levoglucosan degradation based on the PMF analysis. This study provides useful information to better understand the effect of biomass burning on the air quality in the Yangtze River Delta region.

[Characteristics of Soil NO Emissions in the Yangtze River Delta Region for Year 2018].

Soil NO emissions represent an important source of atmospheric nitric oxide (NO) and play an important role in atmospheric chemistry. Based on the latest BDSNP algorithm, this study estimated the soil NO emissions over the Yangtze River Delta region for the year 2018 and further analyzed the associated temporal and spatial variations and uncertainties. The results showed that the annual soil NO emissions in 2018 over the YRD region was 213.6 kt, accounting for 7.3% of the total anthropogenic NOx emissions. Areas with high emissions were mainly concentrated in northern Anhui Province and most parts of Jiangsu Province. In terms of monthly variations, soil NO emissions peaked in June, accounting for 19.9% of the annual emissions and 19.7% of anthropogenic NOx emissions in June. In terms of daily variations, soil NO emissions peaked around 16:00 and accounted for 5.5% of daily emissions. Soil NO emissions came from three components:soil background, nitrogen fertilizer application, and nitrogen deposition. Nitrogen fertilizer application was the main source of soil NO emissions, accounting for up to 77.8%. With the in-depth reduction in NOx emissions from motor vehicles and industries, the importance of soil NO emissions will become increasingly prominent.

Modeling the impacts of land use/land cover change on meteorology and air quality during 2000-2018 in the Yangtze River Delta region, China.

The land use/land cover (LULC) change in the fast-developing city clusters of China exhibits impacts on both the meteorology and air quality. However, this effect, especially in the Yangtze River Delta (YRD), has not been well quantified. In this study, the LULC data are extracted from Landsat satellite imageries for year 2000 and 2018 for the YRD region. The Weather Research and Forecasting with Chemistry (WRF/Chem) model is applied to investigate the impact of historical LULC change on regional meteorology and air pollution over the YRD region during the past two decades. Two simulation scenarios are performed with two sets of LULC data to represent the pre-urbanization (LULC of year 2000) and the most recent urban pattern (LULC of year 2018). Results indicate that rapid urbanization leads to an increase of monthly mean 2-m temperature by 0.4-2.1 °C but decrease of the 10-m wind speed by 0.5-1.3 m/s in urban areas; the maximum increase of daytime planetary boundary layer height (PBLH) in July and November is 289 and 132 m, respectively. Affected by favorable changes in the meteorological conditions due to LULC change, the PM2.5 concentrations in most urban areas show a decreasing trend, especially during the nighttime in summer. On the contrary, surface ozone (O3) concentration in urban areas has increased by 7.2-9.8 ppb in summer and 1.9-2.1 ppb in winter. Changes in O3 concentration are inversely proportional to changes in NOx and the spatial distribution of PM2.5. Areas with higher O3 concentration are consistent with areas of higher temperature and lower wind speed. Our findings reveal that LULC changes during the past years bring observable changes in air pollutant concentrations, which should not be neglected in the YRD region regarding air quality trends as well as policy evaluations under the warming threat.

Highly time-resolved measurements of elements in PM2.5 in Changzhou, China: Temporal variation, source identification and health risks.

The temporal variation, sources, and health risks of elemental composition in fine particles (PM2.5) were explored using online measurements of 19 elements with a time resolution of 1 h at an urban location in Changzhou, China, from December 10, 2020 to March 31, 2021. The mass concentration of PM2.5 was 50.1 ±â€¯32.6 µg m-3, with a range of 3-218 µg m-3. The total concentration of 19 elements (2568 ±â€¯1839 ng m-3) accounted for 5.1 % of PM2.5 mass concentration. S, Cl, Si, and Fe were the dominant elementary species, accounting for 90 % of total element mass concentrations during the whole campaign. Positive matrix factorization (PMF) model was applied to identify the major emission sources of elements in PM2.5. Seven factors, named secondary sulfate mixed with coal combustion, Cl-rich, traffic, iron and steel industry, soil dust, fireworks, and shipping, were identified. The major sources for elements were iron and steel industry, followed by soil dust and secondary sulfate mixed with coal combustion, explaining 32.0 %, 23.5 % and 16.7 % of the total source contribution, respectively. The total hazard index (HI) of elements was 3.01 for children and 1.18 for adults, much greater than the admissible level (HI = 1). The total carcinogenic risk (CR) in Changzhou was estimated to be 5.87 × 10-5, which was above the acceptable CR level (1 × 10-6). Among the calculated metal elements, Cr, Co and As have higher carcinogenic risk, and Co was found to trigger the highest noncarcinogenic risk to Children. Our results indicate that industrial emission is the dominant CR contributor, emphasizing the necessity for stringent regulation of industry sources. Overall, our study provides useful information for policymakers to reduce emissions and health risks from elements in the Yangtze River Delta region.