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Chlorine species play a crucial role as precursors to Cl radicals, which can significantly impact the atmospheric oxidation capacity and influence the levels of trace gases related to climate and air quality. Several studies have established a chlorine emission inventory in China in recent years, but the emission remains uncertain and requires further investigation. The Anthropogenic Chlorine Emission Inventory for China (ACEIC) was the first chlorine emission inventory for China based on local data developed in our previous study, which only includes the emissions from coal combustion and waste incineration. In this study, we updated this inventory to include data for a more recent year (2019) and expanded the range of species considered (HCl, fine particulate Cl−, Cl2, and hypochlorous acid (HOCl)) and the number of anthropogenic sources (41 specific sources). Compared with previous studies, this updated inventory considered more anthropogenic sources, used more localized emission factors, and adopted more refined estimation methods. The total emissions of HCl, fine particulate Cl−, Cl2, and HOCl in mainland China for the year 2019 were estimated to be 361 (−18 % to 27 %), 174 (−27 % to 59 %), 18 (−10 % to 15 %), and 79 (−12 % to 18 %) Gg, respectively. To facilitate analysis, we aggregated the chlorine emissions from various sources into five economic sectors: power, industry, residential, agriculture, and biomass burning. HCl emissions were primarily derived from the industry (43 %), biomass burning (38 %), and residential (13 %) sectors. The biomass burning and industry sectors accounted for 74 % and 19 % of the fine particulate Cl− emissions, respectively. Residential and industry sectors contributed 61 % and 29 % of the total Cl2 emissions. HOCl emissions were predominantly from the residential sector, constituting 90 % of the total emissions. Notably, the usage of chlorine-containing disinfectants was identified as the most significant source of Cl2 and HOCl emissions in the residential sector. Geographically, regions with high HCl and fine particulate Cl− emissions were found in the North China Plain, northeastern China, central China, and the Yangtze River Delta, whereas the Pearl River Delta, Yangtze River Delta, and Beijing–Tianjin–Hebei regions exhibited elevated levels of Cl2 and HOCl emissions. Regarding monthly variation, emissions of HCl and fine particulate Cl− were higher during early spring (February to April) and winter (December to January) due to intensified agricultural activities, while Cl2 and HOCl emissions were higher in the summer months due to increased demand for water disinfection. We incorporated this emission inventory into the chemical transport model and found the simulated concentrations of chlorine species agreed reasonably well with the observations, which suggested the relatively faithful estimations of their emissions. This updated inventory contributes to a better understanding of anthropogenic sources of chlorine species and can aid in the formulation of emission control strategies to mitigate secondary pollution in China.

The past decade has been a boom in lunar exploration. China, India, Japan and other countries have successfully landed landers or rovers on the lunar surface (Wu et al., 2014, 2018, 2020; Prasad et al., 2023). Future missions to explore the Moon are focusing on the lunar south pole (Peña-Asensio et al., 2024). The solar altitude angle at the lunar south pole is extremely low, resulting in low solar irradiance and large areas often in dim light or shadows. The permanently shadowed regions (PSRs) at the lunar south pole are also likely containing substantial amounts of water ice (Li et al., 2018). Future lunar robots exploring the lunar south pole will need to operate in low light or shadowed regions, making camera sensors sensitive to the dim-light environments necessary for these robots. Common night vision sensors usually use near-infrared cameras. However, sensors based on passive infrared technology have image resolution limited by several factors, including the intensity of infrared radiation emitted by the object, the sensitivity of the camera, and the performance of the optical system. For instance, thermal imagers typically have a resolution of 388*284 pixels only. We have developed a dim-light adaptive camera (DimCam) that is ultra-sensitive to the varying illumination conditions driven by AI to achieve high-definition imaging of 1080P or above, for future lunar robots operating in shadows or dim-light regions. The DimCam integrates two starlight-level ultra-sensitive imaging sensors connected by a rigid base to provide stereo vision in low illumination environment. An AI edge computing unit is embedded inside the DimCam to adaptively denoise and enhance image quality. The AI module uses an end-to-end image denoising network to identify and remove noises in the images more accurately by utilizing depth information from the stereo sensors. Compared with traditional monocular denoising algorithms, the denoising network based on stereo vision can significantly improve denoising effects and efficiency by enhancing the signal-to-noise ratio of the data input in the front end. The superposition of overlapping scenes can be regarded as a delayed exposure. Concurrently, the residual analysis of the aligned images aids in noise identification. In addition, for pixels obscured by noise, more accurate pixel values can be restored through interpolation or replacement using depth information obtained from the stereo sensors. Subsequently, a pre-trained lightweight deep network modified from Zero-DCE (Guo et al., 2020) is used for image quality enhancement in terms of brightness and contrast, providing high-quality images even in low-light environments for subsequent applications, such as positioning and navigation of robots, 3D mapping of the surrounding environment, and autonomous driven. We have tested the DimCam in a simulated environment in the laboratory, and the results show that the DimCam has promising performances and great potential for various applications.

Despite significant advancements in improving the dataset for biomass burning (BB) emissions over the past few decades, uncertainties persist in BB aerosol emissions, impeding the accurate assessment of simulated aerosol optical properties (AOPs) and direct radiative forcing (DRF) during wildfire events in global and regional models. This study assessed AOPs (including aerosol optical depth (AOD), aerosol absorption optical depth (AAOD), and aerosol extinction coefficients (AECs)) and DRF using eight independent BB emission inventories applied to the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) during the BB period (March 2019) in peninsular Southeast Asia (PSEA), where the eight BB emission inventories were the Global Fire Emissions Database version 4.1s (GFED), Fire INventory from NCAR version 1.5 (FINN1.5), the Fire Inventory from NCAR version 2.5 MOS (MODIS fire detections; FINN2.5 MOS), the Fire Inventory from NCAR version 2.5 MOSVIS (MODIS + VIIRS fire detections; FINN2.5 MOSVIS), Global Fire Assimilation System version 1.2s (GFAS), Fire Energetics and Emissions Research version 1.0 (FEER), Quick Fire Emissions Dataset version 2.5 release 1 (QFED), and Integrated Monitoring and Modelling System for Wildland FIRES project version 2.0 (IS4FIRES), respectively. The results show that in the PSEA region, organic carbon (OC) emissions in the eight BB emission inventories differ by a factor of about 9 (0.295–2.533 Tg M−1), with 1.09 ± 0.83 Tg M−1 and a coefficient of variation (CV) of 76 %. High-concentration OC emissions occurred primarily in savanna and agricultural fires. The OC emissions from the GFED and GFAS are significantly lower than the other inventories. The OC emissions in FINN2.5 MOSVIS are approximately twice as high as those in FINN1.5. Sensitivity analysis of AOD simulated by WRF-Chem to different BB emission datasets indicated that the FINN scenarios (v1.5 and 2.5) significantly overestimate AOD compared to observation (VIIRS), while the other inventories underestimate AOD in the high-AOD (HAOD; AOD > 1) regions range from 15–22.5∘ N, 97–110∘ E. Among the eight schemes, IS4FIRES and FINN1.5 performed better in terms of AOD simulation consistency and bias in the HAOD region when compared to AERONET sites. The AAOD in WRF-Chem during the PSEA wildfire period was assessed, using satellite observations (TROPOMI) and AERONET data, and it was found that the AAOD simulated with different BB schemes did not perform as well as the AOD. The significant overestimation of AAOD by FINN (v1.5 and 2.5), FEER, and IS4FIRES schemes in the HAOD region, with the largest overestimation for FINN2.5 MOSVIS. FINN1.5 schemes performed better in representing AAOD at AERONET sites within the HAOD region. The simulated AOD and AAOD from FINN2.5 MOSVIS always show the best correlation with the observations. AECs simulated by WRF-Chem with all the eight BB schemes trends were consistent with CALIPSO in the vertical direction (0.5 to 4 km), demonstrating the efficacy of the smoke plume rise model used in WRF-Chem to simulate smoke plume heights. However, the FINN (v1.5 and 2.5) schemes overestimated AECs, while the other schemes underestimated it. In the HAOD region, BB aerosols exhibited a daytime shortwave radiative forcing of −32.60 ± 24.50 W m−2 at the surface, positive forcing (1.70 ± 1.40 W m−2) in the atmosphere, and negative forcing (−30.89 ± 23.6 W m−2) at the top of the atmosphere. Based on the analysis, FINN1.5 and IS4FIRES are recommended for accurately assessing the impact of BB on air quality and climate in the PSEA region.

Nighttime ozone in the lower boundary layer regulates atmospheric chemistry and surface ozone air quality, but our understanding of its vertical structure and impact is largely limited by the extreme sparsity of direct measurements. Here we present 3-year (2017–2019) measurements of ozone in the lower boundary layer (up to 500 m) from the Canton Tower in Guangzhou, the core megacity in South China, and interpret the measurements with a 1-month high-resolution chemical simulation from the Community Multiscale Air Quality (CMAQ) model. Measurements are available at 10, 118, 168, and 488 m, with the highest (488 m) measurement platform higher than the typical height of the nighttime stable boundary layer that allows direct measurements of ozone in the nighttime residual layer (RL). We find that ozone increases with altitude in the lower boundary layer throughout the day, with a vertical ozone gradient between the 10 and 488 m heights (ΔO3/ΔH10–488 m) of 3.6–6.4 ppbv hm−1 in nighttime and 4.4–5.8 ppbv hm−1 in daytime. We identify a high ozone residual ratio, defined as the ratio of ozone concentration averaged over nighttime to that in the afternoon (14:00–17:00 LT), of 69 %–90 % in January, April, and October, remarkably higher than that in the other three layers (29 %–51 %). Ozone in the afternoon convective mixing layer provides the source of ozone in the RL, and strong temperature inversion facilitates the ability of RL to store ozone from the daytime convective mixing layer. The tower-based measurement also indicates that the nighttime surface Ox (Ox= O3+NO2) level can be an effective indicator of RL ozone if direct measurement is not available. We further find significant influences of nocturnal RL ozone on both the nighttime and the following day's daytime surface ozone air quality. During the surface nighttime ozone enhancement (NOE) event, we observe a significant decrease in ozone and an increase in NO2 and CO at the 488 m height, in contrast to their changes at the surface, a typical feature of enhanced vertical mixing. The enhanced vertical mixing leads to an NOE event by introducing ozone-rich and NOx-poor air into the RL to enter the nighttime stable boundary layer. The CMAQ model simulations also demonstrate an enhanced positive contribution of vertical diffusion (ΔVDIF) to ozone at the 10 and 118 m heights and a negative contribution at the 168 and 488 m heights during the NOE event. We also observe a strong correlation between nighttime RL ozone and the following day's surface maximum daily 8 h average (MDA8) ozone. This is tied to enhanced vertical mixing with the collapse of nighttime RL and the development of a convective mixing layer, which is supported by the CMAQ diagnosis of the ozone budget, suggesting that the mixing of ozone-rich air from nighttime RL downward to the surface via the entrainment is an important mechanism for aggravating ozone pollution the following day. We find that the bias in CMAQ-simulated surface MDA8 ozone the following day shows a strong correlation coefficient (r= 0.74) with the bias in nighttime ozone in the RL, highlighting the necessity to correct air quality model bias in the nighttime RL ozone for accurate prediction of daytime ozone. Our study thus highlights the value of long-term tower-based measurements for understanding the coupling between nighttime ozone in the RL, surface ozone air quality, and boundary layer dynamics.

In this study, three methods, i.e., the random forest (RF) algorithm, boosted regression trees (BRTs) and the improved complete ensemble empirical-mode decomposition with adaptive noise (ICEEMDAN), were adopted for investigating emission-driven interannual variations in concentrations of air pollutants including PM2.5, PM10, O3, NO2, CO, SO2 and NO2 + O3 monitored in six cities in South China from May 2014 to April 2021. The first two methods were used to calculate the deweathered hourly concentrations, and the third one was used to calculate decomposed hourly residuals. To constrain the uncertainties in the calculated deweathered or decomposed hourly values, a self-developed method was applied to calculate the range of the deweathered percentage changes (DePCs) of air pollutant concentrations on an annual scale (each year covers May to the next April). These four methods were combined together to generate emission-driven trends and percentage changes (PCs) during the 7-year period. Consistent trends between the RF-deweathered and BRT-deweathered concentrations and the ICEEMDAN-decomposed residuals of an air pollutant in a city were obtained in approximately 70 % of a total of 42 cases (for seven pollutants in six cities), but consistent PCs calculated from the three methods, defined as the standard deviation being smaller than 10 % of the corresponding mean absolute value, were obtained in only approximately 30 % of all the cases. The remaining cases with inconsistent trends and/or PCs indicated large uncertainties produced by one or more of the three methods. The calculated PCs from the deweathered concentrations and decomposed residuals were thus combined with the corresponding range of DePCs calculated from the self-developed method to gain the robust range of DePCs where applicable. Based on the robust range of DePCs, we identified significant decreasing trends in PM2.5 concentration from 2014 to 2020 in Guangzhou and Shenzhen, which were mainly caused by the reduced air pollutant emissions and to a much lesser extent by weather perturbations. A decreasing or probably decreasing emission-driven trend was identified in Haikou and Sanya with inconsistent PCs, and a stable or no trend was identified in Zhanjiang with positive PCs. For O3, a significant increasing trend from 2014 to 2020 was identified in Zhanjiang, Shenzhen, Guangzhou and Haikou. An increasing trend in NO2 + O3 was also identified in Zhanjiang and Guangzhou and an increasing or probably increasing trend in Haikou, suggesting the contributions from enhanced formation of O3. The calculated PCs from using different methods implied that the emission changes in O3 precursors and the associated atmospheric chemistry likely played a dominant role than did the perturbations from varying weather conditions. Results from this study also demonstrated the necessity of combining multiple decoupling methods in generating emission-driven trends in atmospheric pollutants.

Surface ozone concentrations typically peak during the daytime, driven by active photochemical production, and decrease gradually after sunset, due to chemical destruction and dry deposition. Here, we report that nocturnal ozone enhancement (NOE, defined as an ozone increase of more than 5 ppbv h−1 in 1 of any 2 adjacent hours between 20:00 and 06:00 LT, local time) events are observed at multiple monitoring sites in China at a high frequency, which has not been recognized in previous studies. We present an overview of the general characteristics of NOE events in China and explore the possible mechanisms based on 6 years of observations from the national monitoring network. We find that the mean annual frequency of NOE events is 41±10 % (i.e., about 140 d would experience an NOE event per year) averaged over all 814 Chinese sites between 2014 and 2019, which is 46 % larger than that over Europe or the United States. The NOE event frequency is higher in industrialized city clusters (>50 %) than in regions with lighter ozone pollution, and it is higher in the warm season (46 %) than in the cold season (36 %), consistent with the spatiotemporal evolution of ozone levels. The mean ozone peak during NOE events reaches 37±6 ppbv in the warm season. The ozone enhancements are within 5–15 ppbv h−1 during 85 % of the NOE events; however, in about 10 % of cases, the ozone increases can exceed 20 ppbv h−1. We propose that high photochemistry-induced ozone during the daytime provides a rich ozone source in the nighttime residual layer, determining the overall high frequency of NOE events in China, and that enhanced atmospheric mixing then triggers NOE events by allowing the ozone-rich air in the residual layer to mix into the nighttime boundary layer. This is supported by our analyses which show that 70 % (65 %) of the NOE events are associated with increases in friction velocity (planetary boundary layer height), indicative of enhanced atmospheric mixing, and also supported by the observed sharp decreases in surface NO2 and CO concentrations with ozone increases in NOE events, a typical signal of mixing with air in the residual layer. Three case studies in Beijing and Guangzhou show that synoptic processes such as convective storms and low-level jets can lead to NOE events by aggravating vertical mixing. Horizontal transport of ozone-rich plumes may also be a supplementary driver of NOE events. Our results summarize, for the first time, the characteristics and mechanism of NOE events in China based on nationwide and long-term observations, and our findings emphasize the need for more direct measurements and modeling studies on the nighttime ozone evolution from the surface to the residual layer.

Accurate prediction of energy requirement is important in formulating diets, but an energy model for Yellow Broiler breeder hens is publicly unavailable. The objective of this study was to establish energy prediction models for the nitrogen-corrected apparent metabolisable energy (AMEn) requirement of different categories of Yellow Broiler breeder hens during the egg-laying period. Data for modelling were collected from research papers, public databases and production data from companies. Breeder hens were generally categorised into three BW types: heavy, medium and light (HBWT, MBWT and LBWT). Published articles were cited for providing coefficients of AMEn maintenance requirement (AMEnm, 101 kcal/kg BW0.75, 423 KJ/kg BW0.75) and growth requirement (AMEng, 5.33 kcal/g, 22.3 KJ/g), respectively. Models of AMEn for egg production (AMEnp) were established from the known daily intake of AMEn (AMEni) and those of maintenance and growth by the factorial approach: AMEnp = AMEni − AMEnm − AMEng. For the three types of hens, AMEnp HBWT (kcal, KJ) = 2.55 kcal (10.7 KJ) × egg mass (EM, g); AMEnp MBWT (kcal, KJ) = 2.70 kcal (11.3 KJ) × EM (g), and AMEnp LBWT (kcal, KJ) = 2.94 kcal (12.3 KJ) × EM (g) were determined. The total AMEni requirements, depending on Gompertz models, were HBWT: BW (g) = 3 144 × e−EXP(−0.162×(week of age (wk)−15.6)); MBWT: BW (g) = 2 526 × e−EXP(−0.333×(wk−19.1)); LBWT: BW (g) = 1 612 × e−EXP(−0.242×(wk−16.5)). Models of egg production, HBWT: egg production (%) = 124 × e−0.017×wk/(1 + e−0.870×(wk−26.2)); MBWT: egg production (%) = 144 × e−0.020×wk/(1 + e−0.751×(wk−24.9)); LBWT: egg production (%) = 163 × e−0.024×wk/(1 + e−0.476×(wk−26.5))) and egg weight for each wk of the three types of hens during the egg-laying period were all established. These models showed good applicability in simulating and predicting the literature or production data.

Particulate matter (PM) pollution in China is an emerging environmental issue which policy makers and the public have increasingly paid attention to. In order to investigate the characteristics, sources, and chemical processes of PM pollution in Guangzhou, field measurements were conducted from 20 November 2017 to 5 January 2018, with a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) and other collocated instruments. Mass concentrations of non-refractory submicron particulate matter (NR-PM1) measured by the ToF-ACSM correlated well with those of PM2.5 or PM1.1 measured by filter-based methods. The organic mass fraction increased from 45 % to 53 % when the air switched from non-pollution periods to pollution episodes (EPs), indicating significant roles of organic aerosols (OAs) during the whole study. Based on the mass spectra measured by the ToF-ACSM, positive matrix factorization (PMF) with the multilinear engine (ME-2) algorithm was performed to deconvolve OA into four factors, including hydrocarbon-like OA (HOA, 12 %), cooking OA (COA, 18 %), semi-volatile oxygenated OA (SVOOA, 30 %), and low-volatility oxygenated OA (LVOOA, 40 %). Furthermore, we found that SVOOA and nitrate were significantly contributed from local traffic emissions while sulfate and LVOOA were mostly attributed to regional pollutants. Comparisons between this work and other previous studies in China show that secondary organic aerosol (SOA) fraction in total OA increases spatially across China from the north to the south. Two distinctly opposite trends for NR-PM1 formation were observed during non-pollution periods and pollution EPs. The ratio of secondary PM (SPM = SVOOA + LVOOA + sulfate + nitrate + ammonium) to primary PM (PPM = HOA + COA + chloride), together with peroxy radicals RO2∗ and ozone, increased with increasing NR-PM1 concentration during non-pollution periods, while an opposite trend of these three quantities was observed during pollution EPs. Furthermore, oxidation degrees of both OA and SOA were investigated using the f44∕f43 space and the results show that at least two OOA factors are needed to cover a large range of f44 and f43 in Guangzhou. Comparisons between our results and other laboratory studies imply that volatile organic compounds (VOCs) from traffic emissions, in particular from diesel combustion and aromatic compounds, are the most likely SOA precursors in Guangzhou. Peroxy radical RO2∗ was used as a tracer for SOA formed through gas-phase oxidation. For non-pollution periods, SOA concentration was reasonably correlated with RO2∗ concentration during both daytime and nighttime, suggesting that gas-phase oxidation was primarily responsible for SOA formation. However, there was no correlation between SOA and RO2∗ in pollution EPs, suggesting a dramatically changed mechanism for SOA formation. This conclusion can also be supported by different features of SOA in a van Krevelen diagram between non-pollution periods and pollution EPs. Furthermore, for pollution EPs, when NR-PM1 mass concentration was divided into six segments, in each segment except for the lowest one SOA concentration was correlated moderately with RO2∗ concentration, suggesting that gas-phase oxidation still plays important roles in SOA formation. The intercepts of the above linear regressions, which likely correspond to the extent of other mechanisms (i.e., heterogeneous and multiphase reactions), increase with increasing NR-PM1 mass concentration. Our results suggest that while gas-phase oxidation contributes predominantly to SOA formation during non-pollution periods, other mechanisms such as heterogeneous and multiphase reactions play more important roles in SOA formation during pollution EPs than gas-phase oxidation.

Spatiotemporal variations of ozone (O3) and nitrogen oxide (NOx) mixing ratios from 14 state-of-the-art chemical transport models (CTMs) are intercompared and evaluated with O3 observations in East Asia, within the framework of the Model Inter-Comparison Study for Asia Phase III (MICS-Asia III). This study was designed to evaluate the capabilities and uncertainties of current CTMs simulations for Asia and to provide multi-model estimates of pollutant distributions. These models were run by 14 independent groups working in China, Japan, South Korea, the United States and other countries/regions. Compared with the previous phase of MICS-Asia (MICS-Asia II), the evaluation with observations was extended from 4 months to 1 full year across China and the western Pacific Rim. In general, model performance levels for O3 varied widely by region and season. Most models captured the key patterns of monthly and diurnal variation of surface O3 and its precursors in the North China Plain and western Pacific Rim but failed to do so for the Pearl River Delta. A significant overestimation of surface O3 was evident from May to September/October and from January to May over the North China Plain, the western Pacific Rim and the Pearl River Delta. Comparisons drawn from observations show that the considerable diversity in O3 photochemical production partly contributed to this overestimation and to high levels of inter-model variability in O3 for North China. In terms of O3 soundings, the ensemble average of models reproduced the vertical structure for the western Pacific, but overestimated O3 levels to below 800 hPa in the summer. In the industrialized Pearl River Delta, the ensemble average presented an overestimation for the lower troposphere and an underestimation for the middle troposphere. The ensemble average of 13 models for O3 did not always exhibit superior performance compared with certain individual models in contrast with its superior value for Europe. This finding suggests that the spread of ensemble-model values does not represent all of the uncertainties of O3 or that most MICS-Asia III models missed key processes. This study improved the performance of modeling O3 in March at Japanese sites compared with MICS-Asia II. However, it overpredicted surface O3 concentrations for western Japan in July, which was not found by MICS-Asia II. Major challenges still remain with regard to identifying the sources of bias in surface O3 over East Asia in CTMs.

Pre-slaughter transport exerts negative effects on broilers’ welfare, meat yield, and meat quality, but little is known about the effect of transport on medium-growing broiler chickens. This study aimed at evaluating the effects of different durations of transport (0, 0.5, 1, 2, and 3h) on stress biomarkers and meat quality of medium-growing Yellow-feathered broiler chickens. One hundred and eighty Chinese Yellow-feathered broilers aged 75days (marketing age), of 2.02kg average BW, were allotted into five groups; each group contained six replicates (six birds/replicate (crate)). Each crate with dimensions 74×55×27cm (length × width × height) was loaded with six birds, that is, 30kg live BW/m2 crate. The tested transport durations increased BW loss (linear, P0.05), but total antioxidant capacity decreased (linear, P

A PRELIMINARY INVESTIGATION ON COMPARISON AND TRANSFORMATION OF SENTINEL-2 MSI AND LANDSAT 8 OLI Timely and accurate earth observation with short revisit interval is usually necessary, especially for emergency response. Currently, several new generation sensors provided with similar channel characteristics have been operated onboard different satellite platforms, including Sentinel-2 and Landsat 8. Joint use of the observations by different sensors offers an opportunity to meet the demands for emergency requirements. For example, through the combination of Landsat and Sentinel-2 data, the land can be observed every 2–3 days at medium spatial resolution. However, differences are expected in radiometric values (e.g., channel reflectance) of the corresponding channels between two sensors. Spectral response function (SRF) is taken as an important aspect of sensor settings. Accordingly, between-sensor differences due to SRFs variation need to be quantified and compensated. The comparison of SRFs shows difference (more or less) in channel settings between Sentinel-2 Multi-Spectral Instrument (MSI) and Landsat 8 Operational Land Imager (OLI). Effect of the difference in SRF on corresponding values between MSI and OLI was investigated, mainly in terms of channel reflectance and several derived spectral indices. Spectra samples from ASTER Spectral Library Version 2.0 and Hyperion data archives were used in obtaining channel reflectance simulation of MSI and OLI. Preliminary results show that MSI and OLI are well comparable in several channels with small relative discrepancy (

Hazardous air pollutants, such as trace elements in particulate matter (PM), are known or highly suspected to cause detrimental effects on human health. To understand the sources and associated risks of PM to human health, hourly time-integrated major trace elements in size-segregated coarse (PM2.5–10) and fine (PM2.5) particulate matter were collected at the industrial city of Foshan in the Pearl River Delta region, China. Receptor modeling of the data set by positive matrix factorization (PMF) was used to identify six sources contributing to PM2.5 and PM10 concentrations at the site. Dominant sources included industrial coal combustion, secondary inorganic aerosol, motor vehicles and construction dust along with two intermittent sources (biomass combustion and marine aerosol). The biomass combustion source was found to be a significant contributor to peak PM2.5 episodes along with motor vehicles and industrial coal combustion. Conditional probability function (CPF) analysis was applied to estimate the source locations using the PMF-resolved source contribution coupled with the surface wind direction data. Health exposure risk of hazardous trace elements (Pb, As, Si, Cr, Mn and Ni) and source-specific values were estimated. The total hazard quotient (HQ) of PM2.5 was 2.09, higher than the acceptable limit (HQ = 1). The total carcinogenic risk (CR) was 3.37 × 10−3 for PM2.5, which was 3 times higher than the least stringent limit (1.0 × 10−4). Among the selected trace elements, As and Pb posed the highest non-carcinogenic and carcinogenic risks to human health, respectively. In addition, our results show that the industrial coal combustion source is the dominant non-carcinogenic and carcinogenic risk contributor, highlighting the need for stringent control of this source. This study provides new insight for policy makers to prioritize sources in air quality management and health risk reduction.

Chlorine radicals can enhance atmospheric oxidation, which potentially increases tropospheric ozone concentration. However, few studies have been done to quantify the impact of chlorine emissions on ozone formation in China due to the lack of a chlorine emission inventory used in air quality models with sufficient resolution. In this study, the Anthropogenic Chlorine Emissions Inventory for China (ACEIC) was developed for the first time, including emissions of hydrogen chloride (HCl) and molecular chlorine (Cl2) from coal combustion and prescribed waste incineration (waste incineration plant). The HCl and Cl2 emissions from coal combustion in China in 2012 were estimated to be 232.9 and 9.4 Gg, respectively, while HCl emission from prescribed waste incineration was estimated to be 2.9 Gg. Spatially the highest emissions of HCl and Cl2 were found in the North China Plain, the Yangtze River Delta, and the Sichuan Basin. Air quality model simulations with the Community Multiscale Air Quality (CMAQ) modeling system were performed for November 2011, and the modeling results derived with and without chlorine emissions were compared. The magnitude of the simulated HCl, Cl2 and ClNO2 agreed reasonably with the observation when anthropogenic chlorine emissions were included in the model. The inclusion of the ACEIC increased the concentration of fine particulate Cl−, leading to enhanced heterogeneous reactions between Cl− and N2O5, which resulted in the higher production of ClNO2. Photolysis of ClNO2 and Cl2 in the morning and the reaction of HCl with OH in the afternoon produced chlorine radicals which accelerated tropospheric oxidation. When anthropogenic chlorine emissions were included in the model, the monthly mean concentrations of fine particulate Cl−, daily maximum 1 h ClNO2, and Cl radicals were estimated to increase by up to about 2.0 µg m−3, 773 pptv, and 1.5 × 103 molecule cm−3 in China, respectively. Meanwhile, the monthly mean daily maximum 8 h O3 concentration was found to increase by up to 2.0 ppbv (4.1 %), while the monthly mean NOx concentration decreased by up to 0.5 ppbv (6.1 %). The anthropogenic chlorine emissions potentially increased the 1 h O3 concentration by up to 7.7 ppbv in China. This study highlights the need for the inclusion of anthropogenic chlorine emission in air quality modeling and demonstrated its importance in tropospheric ozone formation.

In the frame of the SWOP (sounding water vapour, ozone, and particle) campaign during the Asian summer monsoon (ASM), ozone and water vapour profiles were measured by balloon-borne sensors launched from Lhasa (29.66° N, 91.14° E, elevation 3650 m), China, in August 2013. In total, 24 soundings were launched, nearly half of which show strong variations in the relationship between ozone and water vapour in the tracer–tracer correlation in the upper troposphere and lower stratosphere (UTLS). For each sounding, 20-day backward trajectories were calculated using the trajectory module of the Chemical Lagrangian Model of the Stratosphere (CLaMS) to analyse these variations. The trajectory calculations demonstrate that three tropical cyclones (tropical storm Jebi, typhoons Utor and Trami), which occurred over the western Pacific Ocean during August 2013, had a considerable impact on the vertical distribution of ozone and water vapour by uplifting marine air masses to altitudes of the ASM anticyclone. Air parcels subsequently arrived at the observation site via two primary pathways: firstly via direct horizontal transport from the location of the typhoon to the station within approximately 3 days, and secondly via transport following the clockwise wind flow of the ASM within a timescale of 1 week. Furthermore, the interplay between the spatial position of the ASM anticyclone and tropical cyclones plays a key role in controlling the transport pathways of air parcels from the boundary layer of the western Pacific to Lhasa in horizontal and vertical transport. Moreover, the statistical analysis shows that the strongest impact by typhoons is found at altitudes between 14.5 and 17 km (365–375 K). Low ozone values (50–80 ppbv) were observed between 370 and 380 K due to the strong vertical transport within tropical cyclones.

Diffraction grating is a fundamental optical element in spectral measurement or source monochromation. A newly designed grating named as two-dimension trapezoidal grating (TG), which not only has non-harmonic diffraction, non-background contaminations, but also has high absolute diffraction efficiency and easy fabrication, was proposed, recently. However, its applications in spectral measurement or source monochromation are limited as its diffraction pattern is more complex than ordinary grating and there is no raytracing simulation tool to effectively analyze and evaluate the property of an optical system with TG. A raytracing model for TG based on the scalar diffraction and scattering theory is proposed to solve the above problem. Diffraction direction and absolute efficiency of each diffraction order are obtained by using mathematical derivation with scattering theory and scalar diffraction theory, respectively, which are the key parts of TG’s raytracing model. Once TG’s raytracing module is added into the optical simulation tool, X-LAB, it offers a new opportunity for design and numerical simulation of optical systems with a TG.

A dose-response study was conducted to investigate the metabolizable energy (ME) requirement for Lingnan chickens from 9 to 15 weeks of age. One thousand two hundred 8-week-old slow-growing yellow-feathered male chickens were allotted to five dietary ME levels (2805, 2897, 2997, 3095 and 3236 kcal/kg). The results revealed that the daily metabolizable energy intake increased (p < 0.01), whereas the feed intake and feed:gain ratio decreased linearly (p < 0.01) with the increment in dietary ME level. The final body weight and daily gain of the highest ME treatment tended (p > 0.05) to be greater than those obtained with the lower ME levels. The fat content in breast muscle showed a quadratic response (p < 0.05) to the increase in dietary energy level. The shear force values of breast muscle in the 2897, 3095 and 3236 kcal/kg treatments were lower (p < 0.05) than those of the 2997 kcal/kg treatment. In conclusion, among the tested ME levels, 3095 kcal/kg was adequate for feed intake, shear force, and plasma uric acid, and 3236 kcal/kg tended to increase the body weight, body gain, and feed conversion ratio of Lingnan males between 9 and 15 weeks of age; further studies are still required for testing higher levels.

This study aimed to establish the optimal dietary zinc requirement of Chinese yellow-feathered Lingnan broiler breeders. A total of 576 breeder hens aged 58 weeks were randomly assigned to six treatments, each with 6 replicates of 16 birds (n = 96/treatment). The hens were fed either a basal diet (22.81 mg/kg Zn) or the same basal diet supplemented with additional 24, 48, 72, 96, and 120 mg Zn/kg up to 65 weeks of age. Compared to the results of birds fed the basal diet (22.81 mg Zn/kg), the dietary supplementation with additional Zn (mg/kg) showed higher egg laying rate (at 48−120 mg), EM (at 96 mg/kg), yolk Zn content (at 24−120 mg/kg), fertility (at 48−120 mg/kg), hatchability (at 48−96 mg/kg), tibial breaking strength (at 24−48 mg/kg), tibial ash content (at 48 mg/kg), serum CuZnSOD activity (at 72 mg/kg) and T-AOC (at 48 mg/kg), and ovarian CuZnSOD and GSH-Px activities (at 96−120 mg/kg), and lower FCR (at 96 mg/kg). The regression model showed that the optimal supplemental Zn for maximal egg laying rate, yolk Zn content, fertility, and hatchability of Chinese yellow-feathered broiler breeders aged 58 to 65 weeks were 71.09, 92.34, 94.44 and 98.65 mg/kg diet, respectively.

The structure of the atmospheric boundary layer (ABL) and its influence on regional air quality over the Pearl River Delta (PRD) were examined through two intensive observations in October 2004 and July 2006. Analytical results show the presence of two types of typical weather conditions associated with poor air quality over the PRD. The first is the warm period before a cold front (WPBCF) and the second is the subsidence period controlled by a tropical cyclone (SPCTC). Two typical low air quality situations, which are affected by WPBCF and SPCTC, and one high air quality situation were analysed in detail. Results showed that continuously low or calm ground winds resulted in the accumulation of pollutants, and sea-land breezes had an important role during low air quality conditions. Data on recirculation factors showed that recirculation was significant during low air quality conditions, and steady transportation occurred during high air quality conditions. The ventilation index and the 24 h average ventilation index during high air quality conditions were significantly higher than those during low air quality conditions. Deep and stable inversion layers inside the ABL remarkably affected low air quality. Surface and low-altitude inversions were usually observed during WPBCF, contrary to during SPCTC, during which only the low-altitude inversion appeared frequently.

In this paper, a novel superpixel-based approach is introduced for unsupervised change detection using remote sensing images. The proposed approach contains three steps: 1) Superpixel segmentation. The simple linear iterative cluster (SLIC) algorithm is applied to obtain lattice-like homogenous superpixels. To avoid discordances of the superpixel boundaries obtained from bi-temporal images, the two images are firstly fused using principle component analysis. And then, the SLIC algorithm is applied on the first three principle components, which contain the main information of the two images. 2) For each superpixel, which is considered as the basic unit of the image space, the multi-dimensional change vector is computed from spectral, textural and structural features. 3) The superpixels are classified into two type: changed and unchanged through two progressive classification processes. The superpixels are firstly cataloged into three types: changed, unchanged and undefined by thresholding the change vectors and a voting process. And then the undefined superpixels are further classified into two classes: changed and unchanged, using a SVM-based classifier, which is trained by the derived changed and unchanged superpixels from the former step. The experiment using Indonesia data set has confirmed that the proposed approach is able to detect the changes automatically, by exploiting multiple change features.

The electronic structure and optical properties of Al-doped ZnO with different concentration in wurtzite phase have been systematically investigated using the Heyd-Scuseria-Ernzerhof (HSE06) hybrid density functional on the basis of density functional theory (DFT). The calculated results show that the lattice parameters change little with Al-doped. The optical band gap and electrical conductivity gradually increase with the increasing of Al doping concentration. In addition, the Al-doped ZnO creates shallow donor states around Fermi level in the conduction band minimum from mainly Al-3s state. The dielectric function, absorption coefficient are predicted. The results show that the absorption peaks of Al-doped ZnO have a blue-shift compared with pure ZnO. Beside this, the absorption of visible light can be enhanced.

As part of the PRIDE-PRD2006 intensive campaign, atmospheric boundary layer (ABL) measurements were performed in Qingyuan, Panyu, and Xinken over the Pearl River Delta (PRD) on 1–30 July 2006. During the summer, the surface winds over the PRD are generally controlled by the south, usually with vertical wind shear at a height of approximately 800 m. Subsidence and precipitation from a tropical cyclone affects the air quality of the PRD. Under subsidence, wind speed in the ABL and the height of the ABL decrease and result in high-level concentrations. When the background wind speed is small or calm, the wind profile in Panyu and Xinken changes dramatically with height, which is perhaps caused by local circulation, such as sea-land breezes. To better understand the ABL of the PRD, simulations that used the Weather Research and Forecasting (WRF) mesoscale model were utilized to analyze the ABL characteristics over the PRD. Based on three types of weather condition simulations (i.e., subsidence days, rainy days, and sunny days), the WRF model revealed that the simulated temperature and wind fields in these three cases were moderately consistent with the measurements. The results showed that diurnal variations of the ABL height on subsidence days and sunny days were obvious, but diurnal variations of the ABL height on rainy days were not apparent. The ABL is obviously affected by local circulation, and the ABL features are different at various stations. A simulation focused on a high pollution episode during the subsidence days on 12–15 July 2006, occurred under high-pressure conditions, accompanied by the tropical cyclone "Bilis". A comparison of the simulated vertical wind fields and temperature structure with the ABL measurements at Xinken, Panyu, and Qingyuan stations found that the modeled and measured atmospheric fields revealed two different types of ABL characteristics over the PRD. When the surface winds over the PRD were light or nearly calm, the local circulation dominated, such as the sea-land breeze at Xinken station and the mountain-valley circulation at Qingyuan station. When the surface winds were strong, the stations were under the same background weather system, and the wind directions were almost the same. Furthermore, the modeled results also suggest that the subsidence by the typhoon "Bilis" had a great impact on the high Air Pollution Index (API).