Beijing, the capital of China, suffers from severe atmospheric aerosol pollution; nevertheless, a comprehensive study of the constituents and sources of PM1 is still lacking, and the differences ...between PM1 and PM2.5 are still unclear. In this study, an intensive observation was conducted to reveal the pollution characteristics of PM1 and PM2.5 in Beijing in autumn. Positive matrix factorization (PMF), backward trajectories and a potential source contribution function (PSCF) model were used to identify the source categories and source areas of PM1 and PM2.5. The results showed that the average concentrations of PM1 and PM2.5 reached 78.20μg/m3 and 95.47μg/m3 during the study period, respectively. PM1 contributed greatly to PM2.5. The PM1/PM2.5 value increased from 73.6% to 90.1% with PM1 concentration growing from <50μg/m3 to >150μg/m3. Higher secondary inorganic aerosol (SIA) proportions (31.3%–70.8%) were found in PM1. The higher fraction of SIA, OC, EC and typical elements in PM1 illustrated that anthropogenic components accumulated more in smaller size particles. Three typical weather patterns causing the heavy pollution in autumn were found as follows: (1) Siberian high and uniform high pressure field, (2) cold front and low-voltage system, and (3) uniform low pressure field. A PMF analysis indicated that secondary aerosols and coal combustion, vehicle, industry, biomass burning, and dust were the important sources of PM, accounting for 53.8%, 8.0%, 13.0%, 13.2% and 12.0% of PM1, respectively, and for 47.5%, 9.9%, 12.4%, 8.4% and 21.8% of PM2.5, respectively. The HYSPLIT and chemical components analysis indicated the potential contribution from biomass burning and fertilization ammonia emissions to PM1 in autumn. The source areas were similar for PM1 and PM1–2.5 under general polluted conditions, but during the heavily polluted periods, the source areas were distributed in farther regions from Beijing for PM1 than for PM1–2.5.
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•Simultaneous observation of PM1 and PM2.5 were conducted.•Chemical composition of PM1 and PM2.5 were investigated.•Three typical weather patterns caused heavy pollutions in autumn.•Five contribution sources were identified for PM1 and PM2.5.•Source areas of PM1 and PM1-2.5 were generally similar, but different during heavy pollution periods.
•First comprehensive ship emission inventory in China including OGVs, RVs and CVs•Full year AIS data of >15billion reports (166,546 vessels) were used for estimation.•Detailed spatial distribution ...and monthly variation of ship emissions were presented.•Emission differences of the major port clusters (BSA, YRD and PRD) were analyzed.•Emissions for the 24 major ports in China were presented.
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Ship exhaust emissions have been considered a significant source of air pollution, with adverse impacts on the global climate and human health. China, as one of the largest shipping countries, has long been in great need of in-depth analysis of ship emissions. This study for the first time developed a comprehensive national-scale ship emission inventory with 0.005°×0.005° resolution in China for 2014, using the bottom-up method based on Automatic Identification System (AIS) data of the full year of 2014. The emission estimation involved 166,546 unique vessels observed from over 15billion AIS reports, covering OGVs (ocean-going vessels), CVs (coastal vessels) and RVs (river vessels). Results show that the total estimated ship emissions for China in 2014 were 1.1937×106t (SO2), 2.2084×106t (NOX), 1.807×105t (PM10), 1.665×105t (PM2.5), 1.116×105t (HC), 2.419×105t (CO), and 7.843×107t (CO2, excluding RVs), respectively. OGVs were the main emission contributors, with proportions of 47%–74% of the emission totals for different species. Vessel type with the most emissions was container (~43.6%), followed by bulk carrier (~17.5%), oil tanker (~5.7%) and fishing ship (~4.9%). Monthly variations showed that emissions from transport vessels had a low point in February, while fishing ship presented two emission peaks in May and September. In terms of port clusters, ship emissions in BSA (Bohai Sea Area), YRD (Yangtze River Delta) and PRD (Pearl River Delta) accounted for ~13%, ~28% and ~17%, respectively, of the total emissions in China. On the contrast, the average emission intensities in PRD were the highest, followed by the YRD and BSA regions. The establishment of this high-spatiotemporal-resolution ship emission inventory fills the gap of national-scale ship emission inventory of China, and the corresponding ship emission characteristics are expected to provide certain reference significance for the management and control of the ship emissions.
Selective macroautophagy is an important protective mechanism against diverse cellular stresses. In contrast to the well-characterized starvation-induced autophagy, the regulation of selective ...autophagy is largely unknown. Here, we demonstrate that Huntingtin, the Huntington disease gene product, functions as a scaffold protein for selective macroautophagy but it is dispensable for non-selective macroautophagy. In Drosophila, Huntingtin genetically interacts with autophagy pathway components. In mammalian cells, Huntingtin physically interacts with the autophagy cargo receptor p62 to facilitate its association with the integral autophagosome component LC3 and with Lys-63-linked ubiquitin-modified substrates. Maximal activation of selective autophagy during stress is attained by the ability of Huntingtin to bind ULK1, a kinase that initiates autophagy, which releases ULK1 from negative regulation by mTOR. Our data uncover an important physiological function of Huntingtin and provide a missing link in the activation of selective macroautophagy in metazoans.
In China, renewable/green electricity, which can provide significant environmental benefits in addition to meeting energy demand, has more non-use value than use-value for electricity consumers, ...because its users have no way to actually own this use-value. To assess the value of renewable electricity and obtain information on consumer preferences, this study estimated the willingness to pay (WTP) of Beijing residents for renewable electricity by employing the contingent valuation method (CVM) and identified the factors which affect their WTP. The survey randomly selected 700 participants, of which 571 questionnaires were valid. Half of respondents were found to have positive WTP for renewable electricity. The average WTP of Beijing residents for renewable electricity is estimated to be 2.7–3.3 US$ (18.5–22.5CNY) per month. The main factors affecting the WTP of the respondents included income, electricity consumption, bid and payment vehicle. Knowledge of and a positive attitude towards renewable energy also resulted in the relatively higher willingness of a respondent to pay for renewable electricity. The proportion of respondents replying “yes” to WTP questions using a mandatory payment vehicle was slightly higher than that for questions using a voluntary vehicle. Lastly, several policy implications of this study are presented.
•Most (54%) of respondents in Beijing have positive WTP to renewable electricity.•The average WTP for renewable electricity ranges from 2.7 to 3.3 US$ monthly.•The main factors affecting the WTP include income, electricity consumption, bid and payment vehicle.•Deployment of renewable electricity can cause considerable benefit.
Variations in biomass-carbon of forest can substantially impact the prediction of global carbon dynamics. The allometric models currently used to estimate forest biomass face limitations, as model ...parameters can only be used for the specific species of confirmed sites. Here, we collected allometric models LnW = a + b*Ln(D) (n = 817) and LnW = a + b*Ln(D
H) (n = 612) worldwide and selected eight variables (e.g., mean annual temperature (MAT), mean annual precipitation (MAP), altitude, aspect, slope, soil organic carbon (SOC), clay, and soil type) to predict parameters a and b using Random Forest. LnW = a + b*Ln(D), drove mainly by climate factors, showed the parameter a range from - 5.16 to - 0.90 VaR explained (model evaluation index): 66.21%, whereas parameter b ranges from 1.84 to 2.68 (VaR explained: 49.96%). Another model LnW = a + b*Ln(D
H), drove mainly by terrain factors, showed the parameter a range from - 5.45 to - 1.89 (VaR explained: 69.04%) and parameter b ranges from 0.43 to 1.93 (VaR explained: 69.53%). Furthermore, we captured actual biomass data of 249 sample trees at six sites for predicted parameters validation, showing the R
(0.87) for LnW = a + b*Ln(D); R
(0.93) for LnW = a + b*Ln(D
H), indicating a better result from LnW = a + b*Ln(D
H). Consequently, our results present four global maps of allometric model parameters distribution at 0.5° resolution and provides a framework for the assessment of forest biomass by validation.
Integrative analysis of multi-omics layers at single cell level is critical for accurate dissection of cell-to-cell variation within certain cell populations. Here we report scCAT-seq, a technique ...for simultaneously assaying chromatin accessibility and the transcriptome within the same single cell. We show that the combined single cell signatures enable accurate construction of regulatory relationships between cis-regulatory elements and the target genes at single-cell resolution, providing a new dimension of features that helps direct discovery of regulatory patterns specific to distinct cell identities. Moreover, we generate the first single cell integrated map of chromatin accessibility and transcriptome in early embryos and demonstrate the robustness of scCAT-seq in the precise dissection of master transcription factors in cells of distinct states. The ability to obtain these two layers of omics data will help provide more accurate definitions of "single cell state" and enable the deconvolution of regulatory heterogeneity from complex cell populations.
In this study, a new approach combining the environment monitoring, model simulation and source apportionment methods was proposed to investigate the impact of vehicular emissions on the PM2.5 ...pollution. The method can identify the contributions of various emission sources to both the primary and secondary particles. A case application was conducted in Beijing, China. An intensive monitoring covering the period of December 2010 to January 2012 was conducted to obtain the detailed chemical components proportions in the total PM2.5. The vehicular emission contributions (VECs) to primary organic aerosols (POA), element carbon (EC), SO2, NOX, NH3, elements and VOC were estimated based on the MM5-CMAQ simulation, factor analysis and references investigation. The VECs to different components and to the total PM2.5 were then calculated. Results showed that there was no clear difference in the total VECs of different seasons. The annual average contribution ratio was approximately 22.5 ± 3.5%. Among all the chemical species, nitrate and SOA accounted for the highest contribution percentages. In addition, the influence of road dust on the PM2.5 pollution was also simulated using the MM5-CMAQ modeling system. It is indicated that the road dust contributed approximately 4.9 ± 1.3% of the total PM2.5 on an annual average. Considering both the contributions from motor vehicles and road dust emissions, the annual average direct contributions from road transport to the PM2.5 in Beijing was approximately 27.4 ± 4.8%.
•A new approach was proposed to track secondary aerosols to primary emission sources.•The vehicular emission contribution to the PM2.5 pollution was estimated.•The influence of road dust was simulated using MM5-CMAQ.•Road transport emissions accounted for about 27.4 ± 4.8% of the PM2.5 in Beijing.
ZnO as high-temperature thermoelectric material suffers from high lattice thermal conductivity and poor electrical conductivity. Al is often used to n-dope ZnO to form Zn1–x Al x O (AZO). Owing to ...very limited Al solubility (less than 2 atom %) in AZO, however, electrical conductivity is difficult to improve further. Moreover, such a low concentration of Al dopants can hardly reduce the thermal conductivity. Here, we propose slightly adding chemically reduced graphene oxides (rGOs) to AZO in various contents to modulate the carrier concentration and simultaneously optimize the electrical and thermal conductivities. Such nanocomposites with rGO embedded in AZO matrix are formed on the molecular level by one-step solution chemistry method. No obvious changes are found in crystalline structures of AZO after introducing rGOs. The rGO inclusions are shown to uniformly mix the AZO matrix that consists of compacted nanoparticles. In such AZO/rGO hybrids, Zn2+ is captured by the rGO, releasing extra electrons and thus increasing electron density, as confirmed by Hall measurements. The phonon-boundary scattering at the interface between AZO and rGO remarkably reduces the lattice thermal conductivity. Therefore, a respectable thermoelectric figure of merit of 0.28 at 900 °C is obtained in these nanocomposites at the rGO content of 1.5 wt %, which is 8 times larger than that of pure ZnO and 60% larger than that of alloyed AZO. This work demonstrates a facile wet chemistry route to produce nanostructured thermoelectric composites in which electrical conductivity can be greatly increased while largely lowering thermal conductivity, collectively enhancing the thermoelectric performance.
Compared with on-road vehicles, emission from ships is one of the least-regulated anthropogenic emission sources and non-negligible source of primary aerosols and gas-phase precursors of PM2.5. The ...Bohai Rim Region in China hosts dozens of large ports, two of which ranked among the top ten ports in the world. To determine the impact of ship emissions on the PM2.5 concentrations over this region, two parts of works have been conducted in this study. First, a detailed ship emission inventory with high spatiotemporal resolution was developed based on Automatic Identification System (AIS) data. Then the WRF/Chem model was applied to modeling the impact of ship emissions by comparing two scenarios: with and without ship emissions. The results indicate that the total estimated ship emissions of SO2, NOX, PM10, PM2.5, CO, HC, and CO2 from Bohai Rim Region in 2014 are 1.9×105, 2.9×105, 2.6×104, 2.4×104, 2.5×104, 1.2×104, and 1.3×107tonnes, respectively. The modeling results indicate that the annual PM2.5 concentrations increased by 5.9% on land areas of Bohai Rim Region (the continent within 115.2°E–124.3°E and 36.1°N–41.6°N) due to ship emissions. The contributions show distinctive seasonal variations of contributions, presenting highest in summer (12.5%) followed by spring (6.9%) and autumn (3.3%), and lowest in winter (0.9%). The contribution reaches up to 10.7% along the shoreline and down to 1.0% 200km inland. After examining the statistics of the modeling results during heavy and non-heavy haze days in July, it was found that 6 out of 9 cities around the Bohai Rim Region were observed with higher contributions from ship emissions during heavy haze days compared with non-heavy haze days. These results indicate that the impacts of ship emissions on the ambient PM2.5 are non-negligible, especially for heavy haze days for most coastal cities in the Bohai Rim Region.
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•Impact of ship emissions on PM2.5 in Bohai Rim Region (BRR) was estimated by WRF/Chem.•Ship emission inventory with high spatiotemporal resolution was developed in the area.•Average contribution of ship emissions to PM2.5 in land areas of BRR was 5.9% in 2014.•The average contributions were 10.7% along the shoreline and down to 1.0% 200km inland.•Ship contributions in most coastal cities were bigger in haze period than other days.
This paper aims to study the vehicular emissions trends in the Beijing–Tianjin–Hebei (BTH) region, located in northern China. The multiyear emission inventories of NOX, CO, VOC and PM10 from road ...vehicles in the period 1999–2010 were developed by the COPERT IV model. Results show that vehicular emissions of CO and VOC have decreased by annual average change rates (AACR) of −3.1% to −5.2% and −4.4% to −6.9% in the study area, respectively. However, due to the rapid development of freight traffic, emissions of NOX and PM10 have kept increasing in Tianjin and Hebei. Based on the vehicular emission inventories, trends of emission levels for vehicles with different standards, as well as the overall effects of implementing vehicular emission mitigation strategies were assessed. It is suggested that passenger cars (PC) with Euro 0 and Euro I standards, which were at higher emission level in the PC fleet, should be gradually eliminated. Although the increasing rates (IR) of emissions from PC were lower than those of the PC population, the sharp growth of PC population in recent years contributed to a remarkable increase of emissions, weakening the overall mitigation effect. Total vehicle population capacity and other mitigation measures should be studied in China in order to develop new and more effective vehicular emission control strategies.
► Vehicular emissions from 1999 to 2010 were estimated in BTH. ► CO and VOC emissions have decreased, while NOX and PM10 emissions kept increasing. ► Overall effects of implementing emission control strategies were assessed. ► High-pollution vehicles should be eliminated. ► Sharp growth of vehicle numbers and freight traffic lead to increasing emissions.
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