Database of emission factors of volatile organic compound (VOC) species in motor vehicle exhaust in China.

The synergistic strategy for fine particulate matter (PM2.5) and O3 pollution prevention and control has emerged as a pivotal approach in combating air pollution. Volatile organic compounds (VOCs) serve as crucial precursors to both O3 and secondary organic aerosols (SOAs), with motor vehicles representing one of their significant sources. In this study, a standard for establishing a database of VOC species emission factors for motor vehicles was developed, and a database containing 134 VOC species was constructed through field tests and literature surveys. The VOC emissions of light-duty gasoline passenger vehicles (LDGPVs) comprised primarily alkanes and aromatics. The VOC emissions of light-duty diesel trucks (LDDTs) comprised mostly alkanes. Regarding low-speed trucks, 3-wheel vehicles, medium-duty diesel trucks (MDDTs) and heavy-duty diesel trucks (HDDTs), their VOC emissions comprised mainly oxygenated volatile organic compounds (OVOCs). The update of emission standards resulted in a reduction in VOC species emission factors while altering the composition of VOCs. Attention should be directed toward isopentane, benzene and dichloromethane emitted by LDGPVs, dodecane, undecane, ethene and propene emitted by LDDTs, and acetaldehyde emitted by HDDTs. VOC species originating from LDGPVs were more dispersed than those originating from LDDTs and HDDTs. In addition, variations in VOC species were observed among motor vehicles with different fuel types. Toluene, ethene, benzene, m,p-xylene, isopentane, hexanal, ethyne and 1,2,4-trimethylbenzene were the predominant VOC species emitted by gasoline vehicles. Diesel vehicles emitted mainly dodecane, formaldehyde, propene, undecane, acetaldehyde, ethene, decane and benzene. The results could enhance our comprehension of the emission characteristics of VOC species originating from motor vehicles and provide data support and a scientific foundation for achieving synergistic PM2.5 and O3 pollution prevention and control.

Characteristics and reduction assessment of GHG emissions from crop residue open burning in China under the targets of carbon peak and carbon neutrality.

Driven by the goal of carbon peak and carbon neutrality, greenhouse gas (GHG) emissions from the crop residue open burning (CROB) in China cannot be ignored. In this study, we have established a high-resolution (0.05° × 0.05°) GHG emissions inventory (including CO2, CH4, and N2O) of CROB from 2012 to 2021 in China based on the VIIRS data and official statistics. To improve the results accuracy, we compared the two commonly used bases for grid allocation, fire counts (FC) and fire radiative power (FRP), in the construction of high-resolution inventory. In 2012, GHG emissions are overestimated by 599 t CO2e per grid on average in 24,577 grids, and underestimated by 1096 t CO2e per grid on average in 13,546 grids based on FC compared to FRP. Then, we characterized the spatial and temporal distribution of GHG emissions from CROB by using the FRP-based method. From 2012 to 2021, total GHG emissions from CROB in China have decreased by 31.2 %, of which the East and South-Central China contributed 22.51 and 9.12 Tg CO2e of GHG reductions, while the Northeast China contributed 10.73 Tg CO2e of GHG growth, respectively. In addition, GHG emissions from CROB on the time scale are mainly concentrated in April, June, and October, with variations between years and regions influenced by the policy, climate, and farmers' perceptions. Finally, we assessed the GHG emission reductions from CROB under different scenarios in the future. By 2060, GHG emissions would be significantly reduced by 57.3 %-77.9 % compared to 2021 under effective control measures. We believe the results will be of great significance for GHG policy formulation and emission reduction potential assessment.

Real-World Emission Characteristics of Full-Volatility Organics Originating from Nonroad Agricultural Machinery during Agricultural Activities.

Nonroad agricultural machinery (NRAM) emissions constitute a significant source of air pollution in China. Full-volatility organics originating from 19 machines under 6 agricultural activities were measured synchronously. The diesel-based emission factors (EFs) for full-volatility organics were 4.71 ± 2.78 g/kg fuel (average ± standard deviation), including 91.58 ± 8.42% volatile organic compounds (VOCs), 7.94 ± 8.16% intermediate-volatility organic compounds (IVOCs), 0.28 ± 0.20% semivolatile organic compounds (SVOCs), and 0.20 ± 0.16% low-volatility organic compounds (LVOCs). Full-volatility organic EFs were significantly reduced by stricter emission standards and were the highest under pesticide spraying activity. Our results also demonstrated that combustion efficiency was a potential factor influencing full-volatility organic emissions. Gas-particle partitioning in full-volatility organics could be affected by multiple factors. Furthermore, the estimated secondary organic aerosol formation potential based on measured full-volatility organics was 143.79 ± 216.80 mg/kg fuel and could be primarily attributed to higher-volatility-interval IVOCs (bin12-bin16 contributed 52.81 ± 11.58%). Finally, the estimated emissions of full-volatility organics from NRAM in China (2021) were 94.23 Gg. This study provides first-hand data on full-volatility organic EFs originating from NRAM to facilitate the improvement of emission inventories and atmospheric chemistry models.

Real-world emission characteristics and inventory of volatile organic compounds originating from construction and agricultural machinery.

Volatile organic compound (VOC) emissions originating from nonroad mobile sources constitute an important but uncertain source of secondary organic aerosols (SOAs) and ozone (O3). In this study, we investigated the emission factors (EFs) of 120 individual VOC species for 40 machines via gas chromatography-mass spectrometry/flame ionization detection and high-performance liquid chromatography. The results showed that the diesel-based VOC EF for the tested machines was 4.18 ± 2.55 (average ± standard deviation) g/kg fuel, dominated by alkanes (38.20 % ± 18.08 %) and oxygenated VOCs (OVOCs; 30.94 % ± 15.71 %). The machine type, rated power, emission standards, and operating conditions affected the emissions of VOCs and their components, and this effect maybe mostly depends on the fuel combustion efficiency. The VOC species were primarily distributed in the C1-C2 and C4-C6 (based on the carbon number) and B4-B6 (based on the saturated vapor concentration) intervals. Furthermore, the estimated formation potential (FP) values of SOAs and O3 from VOCs were 21.02 ± 15.57 mg/kg fuel and 15.96 ± 11.87 g/kg fuel, respectively. VOC control based on the SOA formation potential (SOAFP) and ozone formation potential (OFP) could be more effective in the mitigation of fine particulate matter (PM2.5) and O3 pollution because the top 5 species ranked by percentage contribution accounted for 83.09 % ± 9.59 % and 51.78 % ± 14.38 % of the estimated SOAFP and OFP, respectively. Finally, the emission estimates showed that the VOC emissions originating from construction and agricultural machinery in China (2020) reached 64.05 and 95.24 Gg, respectively. We provide species-specific VOC EFs and detailed emission characteristics to facilitate a comprehensive understanding of gas emissions originating from nonroad mobile sources and an update of emission inventories and atmospheric chemistry models.

Reduced soil multifunctionality and microbial network complexity in degraded and revegetated alpine meadows.

Understanding how microbial processes develop and change in alpine meadow soils is key to global initiatives toward environmental sustainability and local land management. Yet, how microbial interactions mediate soil multifunctionality in disturbed and managed alpine meadows remains understudied. Here, we investigated multiple community metrics, particularly microbial network properties and assembly processes, of soil bacterial and fungal communities and their links to certain soil functions along a degradation-restoration sequence of alpine meadows in the Qinghai-Tibetan Plateau. Meadow degradation caused significant declines in soil hydraulic conductivity (e.g., higher bulk density, reduced soil porosity and water content) and nitrogen availability, leading to lowered soil multifunctionality. Meadow degradation only caused weak changes in microbial abundance, alpha diversity, and community composition, but remarkably reduced bacterial network complexity, to a less extent for fungal network properties. Short-term artificial restoration with productive grass monocultures did not restore soil multifunctionality, in turn even destabilized bacterial network and favored pathogenic over mutualistic fungi. Soil fungi community are more stable than bacteria in disturbed alpine meadows, and they evolved with distinct assembly strategies (stochastic-dominant versus deterministic-driven processes, respectively). Further, microbial network complexity, positively and better predicts soil multifunctionality than alpha diversity. Our work shows how microbial interaction complexity may enhance soil multifunctionality in degraded alpine meadow ecosystems, noting that meadow restoration with low plant species diversity may failed in restoring multiple ecosystem functions. These findings would help predict the outcomes of global environmental changes and inform management strategies in regional grassland conservation and restoration.

Chemical characterization of volatile organic compounds (VOCs) emitted from multiple cooking cuisines and purification efficiency assessments.

Cooking process can produce abundant volatile organic compounds (VOCs), which are harmful to environment and human health. Therefore, we conducted a comprehensive analysis in which VOCs emissions from multiple cuisines have been sampled based on the simulation and acquisition platform, involving concentration characteristics, ozone formation potential (OFP) and purification efficiency assessments. VOCs emissions varied from 1828.5 to 14,355.1 µg/m3, with the maximum and minimum values from Barbecue and Family cuisine, respectively. Alkanes and alcohol had higher contributions to VOCs from Sichuan and Hunan cuisine (64.1%), Family cuisine (66.3%), Shandong cuisine (69.1%) and Cantonese cuisine (69.8%), with the dominant VOCs species of ethanol, isobutane and n-butane. In comparison, alcohols (79.5%) were abundant for Huaiyang cuisine, while alkanes (19.7%), alkenes (35.9%) and haloalkanes (22.9%) accounted for higher proportions from Barbecue. Specially, carbon tetrachloride, n-hexylene and 1-butene were the most abundant VOCs species for Barbecue, ranging from 8.8% to 14.6%. The highest OFP occurred in Barbecue. The sensitive species of OFP for Huaiyang cuisine were alcohols, while other cuisines were alkenes. Purification efficiency assessments shed light on the removal differences of individual and synergistic control technologies. VOCs emissions exhibited a strong dependence on the photocatalytic oxidation, with the removal efficiencies of 29.0%-54.4%. However, the high voltage electrostatic, wet purification and mechanical separation techniques played a mediocre or even counterproductive role in the VOCs reduction, meanwhile collaborative control technologies could not significantly improve the removal efficiency. Our results identified more effective control technologies, which were conductive to alleviating air pollution from cooking emissions.

Classification for thyroid nodule using ViT with contrastive learning in ultrasound images.

The lack of representative features between benign nodules, especially level 3 of Thyroid Imaging Reporting and Data System (TI-RADS), and malignant nodules limits diagnostic accuracy, leading to inconsistent interpretation, overdiagnosis, and unnecessary biopsies. We propose a Vision-Transformer-based (ViT) thyroid nodule classification model using contrast learning, called TC-ViT, to improve accuracy of diagnosis and specificity of biopsy recommendations. ViT can explore the global features of thyroid nodules well. Nodule images are used as ROI to enhance the local features of the ViT. Contrast learning can minimize the representation distance between nodules of the same category, enhance the representation consistency of global and local features, and achieve accurate diagnosis of TI-RADS 3 or malignant nodules. The test results achieve an accuracy of 86.9%. The evaluation metrics show that the network outperforms other classical deep learning-based networks in terms of classification performance. TC-ViT can achieve automatic classification of TI-RADS 3 and malignant nodules on ultrasound images. It can also be used as a key step in computer-aided diagnosis for comprehensive analysis and accurate diagnosis. The code will be available at https://github.com/Jiawei217/TC-ViT.

Real-world emission characteristics of semivolatile/intermediate-volatility organic compounds originating from nonroad construction machinery in the working process.

Detailed emission characterization of semivolatile/intermediate-volatility organic compounds (S/IVOCs) originating from nonroad construction machines (NRCMs) remains lacking in China. Twenty-one NRCMs were evaluated with a portable emission measurement system in the working process. Gas phase S/IVOCs were collected by Tenax TA tubes and analyzed via thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Particle phase S/IVOCs were collected by quartz filters and analyzed via GC-MS. The average emission factors (EFs) for fuel-based total (gas + particle phase) IVOCs and SVOCs of the assessed NRCMs were 221.45 ± 194.60 and 11.68 ± 10.67 mg/kg fuel, respectively. Compared to excavators, the average IVOC and SVOC EFs of loaders were 1.32 and 1.55 times higher, respectively. Compared to the working mode, the average IVOC EFs under the moving mode (only moving forward or backward) were 1.28 times higher. The IVOC and SVOC EFs for excavators decreased by 69.06% and 38.37%, respectively, from China II to China III. These results demonstrate the effectiveness of emission control regulations. In regard to individual NRCMs, excavators and loaders were affected differently by emission standards. The volatility distribution demonstrated that IVOCs and SVOCs were dominated by gas- and particle-phase compounds, respectively. The mode of operation also affected S/IVOC gas-particle partitioning. Combined with previous studies, the mechanical type significantly affected the volatility distribution of IVOCs. IVOCs from higher volatile fuels are more distributed in the high-volatility interval. The total secondary organic aerosol (SOA) production potential was 104.36 ± 79.67 mg/kg fuel, which originated from VOCs (19.98%), IVOCs (73.87%), and SVOCs (6.15%). IVOCs were a larger SOA precursor than VOCs and SVOCs. In addition, normal (n-) alkanes were suitably correlated with IVOCs, which may represent a backup solution to quantify IVOC EFs. This work provides experimental data support for the refinement of the emission characteristics and emission inventories of S/IVOCs originating from NRCMs.

Emission characteristics and inventory of volatile organic compounds from the Chinese cement industry based on field measurements.

Volatile organic compounds (VOCs) are major precursors of ozone (O3) and secondary organic aerosols (SOA), which degrade air quality and pose a serious risk to human health and ecological systems. Previous studies on the emission characteristics of VOCs have predominantly focused on petrochemical and solvent-using sources, while localized studies on the cement industry are scarce in China. Field measurements for four cement plants were carried out in this study to investigate the emission levels, source profiles, and secondary pollutant generation potential of 98 VOCs species emitted from rotary and shaft kilns in China. Furthermore, a species-differentiated VOCs emission inventory was compiled for the Chinese cement industry in 2019. The results demonstrated that the mass concentration of VOCs emitted from shaft kiln was more than 20-fold higher than that emitted from rotary kilns, and the alkanes was the dominant species (56%) in shaft kilns, while oxygenated VOCs (OVOCs) and halocarbons were the main species in rotary kilns. Moreover, alkenes & alkyne were the dominant contributors to ozone formation potential (OFP) in shaft kilns, whereas alkenes & alkyne and OVOCs were comparable and prominent contributors in rotary kilns. In contrast, secondary organic aerosol potential (SOAP) for the two types of kilns was dominated by aromatics. In 2019, approximately 18.18 kt VOCs were emitted from cement production and were found to be largely concentrated in the southeast and central provinces of China. Considering the influence on environmental conditions, high OFP-contributing species in cement kilns are suggested to be a priority in the pollution mitigation of O3. This study provides a new, comprehensive, and reasonable cognition of the current VOCs emissions from both rotary and shaft kilns in China, which will aid in a better understanding of VOCs emission characteristics and guide future policy-making.

Vehicle emissions of primary air pollutants from 2009 to 2019 and projection for the 14th Five-Year Plan period in Beijing, China.

Over the past decade, the emission standards and fuel standards in Beijing have been upgraded twice, and the vehicle structure has been improved by accelerating the elimination of 2.95 million old vehicles. Through the formulation and implementation of these policies, the emissions of carbon monoxide (CO), volatile organic compounds (VOCs), nitrogen oxides (NOx), and fine particulate matter (PM2.5) in 2019 were 147.9, 25.3, 43.4, and 0.91 kton in Beijing, respectively. The emission factor method was adopted to better understand the emissions characteristics of primary air pollutants from combustion engine vehicles and to improve pollution control. In combination with the air quality improvement goals and the status of social and economic development during the 14th Five-Year Plan period in Beijing, different vehicle pollution control scenarios were established, and emissions reductions were projected. The results show that the emissions of four air pollutants (CO, VOCs, NOx, and PM2.5) from vehicles in Beijing decreased by an average of 68% in 2019, compared to their levels in 2009. The contribution of NOx emissions from diesel vehicles increased from 35% in 2009 to 56% in 2019, which indicated that clean and energy-saving diesel vehicle fleets should be further improved. Electric vehicle adoption could be an important measure to reduce pollutant emissions. With the further upgrading of vehicle structure and the adoption of electric vehicles, it is expected that the total emissions of the four vehicle pollutants can be reduced by 20%-41% by the end of the 14th Five-Year Plan period.

Real-world emission characteristics of carbonyl compounds from agricultural machines based on a portable emission measurement system.

Emissions of carbonyl compounds from agricultural machines cannot be ignored. Carbonyl compounds can cause the formation of ozone (O3) and secondary organic aerosols, which can cause photochemical smog to form. In this study, 20 agricultural machines were tested using portable emission measurement system (PEMS) under real-world tillage processes. The exhaust gases were sampled using 2,4-dinitrophenylhydrazine cartridges, and 15 carbonyl compounds were analyzed by high-performance liquid chromatography. Carbonyl compound emission factors for agricultural machines were 51.14-3315.62 mg/(kg-fuel), and were 2.58 ± 2.05, 0.86 ± 1.07 and 0.29 ± 0.20 g/(kg-fuel) for China 0, China II and China III emission standards, respectively. Carbonyl compound emission factor for sowing seeds of China 0 agricultural machines was 3.32 ± 1.73 g/(kg-fuel). Formaldehyde, acetaldehyde and acrolein were the dominant carbonyl compounds emitted. Differences in emission standards and tillage processes impact ozone formation potential (OFP). The mean OFP was 20.15 ± 16.15 g O3/(kg-fuel) for the China 0 emission standard. The OFP values decreased by 66.9% from China 0 to China II, and 67.4% from China II to China III. The mean OFP for sowing seeds of China 0 agricultural machines was 25.92 ± 13.84 g O3/(kg-fuel). Between 1.75 and 24.22 times more ozone was found to be formed during sowing seeds than during other processes for China 0 and China II agricultural machines. Total carbonyl compound emissions from agricultural machines in China was 19.23 Gg in 2019. The results improve our understanding of carbonyl compound emissions from agricultural machines in China.

Spatial-temporal heterogeneity and driving factors of PM2.5 in China: A natural and socioeconomic perspective.

Background: Fine particulate matter (PM2.5), one of the major atmospheric pollutants, has a significant impact on human health. However, the determinant power of natural and socioeconomic factors on the spatial-temporal variation of PM2.5 pollution is controversial in China. Methods: In this study, we explored spatial-temporal characteristics and driving factors of PM2.5 through 252 prefecture-level cities in China from 2015 to 2019, based on the spatial autocorrelation and geographically and temporally weighted regression model (GTWR). Results: PM2.5 concentrations showed a significant downward trend, with a decline rate of 3.58 µg m-3 a-1, and a 26.49% decrease in 2019 compared to 2015, Eastern and Central China were the two regions with the highest PM2.5 concentrations. The driving force of socioeconomic factors on PM2.5 concentrations was slightly higher than that of natural factors. Population density had a positive significant driving effect on PM2.5 concentrations, and precipitation was the negative main driving factor. The two main driving factors (population density and precipitation) showed that the driving capability in northern region was stronger than that in southern China. North China and Central China were the regions of largest decline, and the reason for the PM2.5 decline might be the transition from a high environmental pollution-based industrial economy to a resource-clean high-tech economy since the implementation the Air Pollution Prevention and Control Action Plan in 2013. Conclusion: We need to fully consider the coordinated development of population size and local environmental carrying capacity in terms of control of PM2.5 concentrations in the future. This research is helpful for policy-makers to understand the distribution characteristics of PM2.5 emission and put forward effective policy to alleviate haze pollution.

Multi-pollutant emission characteristics of non-road construction equipment based on real-world measurement.

Non-road construction equipment (NRCE) has become a crucial contributor to urban air pollution. However, the current research on NRCE is still in its infancy, and the understanding of its pollutant emissions is not yet clear. In this study, multi-pollutant (CO, HC, NOx, PM2.5, and BC) and CO2 emissions from 12 excavators and 9 loaders under real-world conditions are investigated by using a synchronous platform based on portable emission measurement system (SP-PEMS). We find the instantaneous emission rates of multi-pollutant present significant variability under different operation modes, and pollutant emissions are significantly high under cold start. Generally, multi-pollutant emission factors (EFs) have been all effectively reduced with the tightening of emission standards except for CO and NOx. The BC and PM2.5 emissions are significantly affected by engine types, and those emitted by electronically-controlled fuel injection (EI) engines are at lower concentration levels compared with mechanical fuel injection (MI) engines. The mass ratios of BC/PM2.5 for EI engines are 2.05 times that for MI engines on average. Through comparison, we find the multi-pollutant EFs of NRCE reported by different studies and the Guide vary greatly, and those recommended by the Guide may be overestimated or underestimated to varying degrees. Finally, we recommend the multi-pollutant EFs of NRCE under different emission standards by combining the results of various studies, and which will provide scientific support for the accurately establish of emission inventory.

Multi-type emission factors quantification of black carbon from agricultural machinery based on the whole tillage processes in China.

Black carbon (BC), as one of the short-lived climate pollutants, is becoming more prominent contribution from non-road mobile source, especially for agricultural machinery (AM) in China. However, the understanding of BC emissions from AM is still not clear, and the BC emission factors (EFs) are also limited. In this study, we conducted real-world measurements on twenty AM to investigate the instantaneous BC emission characteristics and quantify BC EFs under the whole tillage processes. We find the instantaneous BC emissions and fuel consumptions are obvious differences and present good synchronization under different tillage processes. Multi-type (CO2-, fuel-, distance-, time-, and area-based) EFs of BC are developed, which are significantly affected by different tillage processes and emission standards of the used AM. While AM conducting rotary tillage, ploughing, harvest corn and harvest wheat on the same area of land, total BC emissions by using the China III emission standard AM will be reduced by 56%, 36%, 88%, and 87% than those by using China II emission standard AM, respectively. Furthermore, for corn and wheat production under the whole tillage processes, BC EFs are 16.90 (6.03-39.12) g/hm2 and 18.18 (5.91-38.69) g/hm2, CO2 EFs are 112.64 (72.07-195.98) g/hm2 and 103.72 (71.47-167.02) g/hm2, respectively. We estimate the BC and CO2 emissions from wheat and corn productions based on the average area-based EFs. The large fluctuation ranges of BC and CO2 emissions in different tillage processes and the whole processes can reflect that the use of AM in China is uneven. It also indicates that there is a large space for BC and CO2 emission reduction and optimization. Therefore, more attention should be paid to the control of BC and CO2 emissions from AM. We believe that the recommended multi-type EFs are applicable for the quantification of BC emissions from AM in China and other countries.

Fine particulate matter (PM2.5/PM1.0) in Beijing, China: Variations and chemical compositions as well as sources.

Particulate matter (i.e., PM1.0 and PM2.5), considered as the key atmospheric pollutants, exerts negative effects on visibility, global climate, and human health by associated chemical compositions. However, our understanding of PM and its chemical compositions in Beijing under the current atmospheric environment is still not complete after witnessing marked alleviation during 2013-2017. Continuous measurements can be crucial for further air quality improvement by better characterizing PM pollution and chemical compositions in Beijing. Here, we conducted simultaneous measurements on PM in Beijing during 2018-2019. Results indicate that annual mean PM1.0 and PM2.5 concentrations were 35.49 ± 18.61 µg/m3 and 66.58 ± 60.17 µg/m3, showing a positive response to emission controls. The contribution of sulfate, nitrate, and ammonium (SNA) played an enhanced role with elevated PM loading and acted as the main contributors to pollution episodes. Discrepancies observed among chemical species between PM1.0 and PM2.5 in spring suggest that sand particles trend to accumulate in the range of 1-2.5 µm. Pollution episodes occurred accompanied with southerly clusters and high formation of SNA by heterogeneous reactions in summer and winter, respectively. Results from positive matrix factorization (PMF) combined with potential source contribution function (PSCF) models showed that potential areas were seasonal dependent, secondary and vehicular sources became much more important compared with previous studies in Beijing. Our study presented a continuous investigation on PM and sources origins in Beijing, which provides a better understanding for further emission control as well as a reference for other cities in developing countries.

Anthropogenic Intensity-Determined Assembly and Network Stability of Bacterioplankton Communities in the Le'an River.

Bacterioplankton are essential components of riverine ecosystems. However, the mechanisms (deterministic or stochastic processes) and co-occurrence networks by which these communities respond to anthropogenic disturbances are not well understood. Here, we integrated niche-neutrality dynamic balancing and co-occurrence network analysis to investigate the dispersal dynamics of bacterioplankton communities along human activity intensity gradients. Results showed that the lower reaches (where intensity of human activity is high) had an increased composition of bacterioplankton communities which induced strong increases in bacterioplankton diversity. Human activity intensity changes influenced bacterioplankton community assembly via regulation of the deterministic-stochastic balance, with deterministic processes more important as human activity increases. Bacterioplankton molecular ecological network stability and robustness were higher on average in the upper reaches (where there is lower intensity of human activity), but a human activity intensity increase of about 10%/10% can reduce co-occurrence network stability of bacterioplankton communities by an average of 0.62%/0.42% in the dry and wet season, respectively. In addition, water chemistry (especially NO3 --N and Cl-) contributed more to explaining community assembly (especially the composition) than geographic distance and land use in the dry season, while the bacterioplankton community (especially the bacterioplankton network) was more influenced by distance (especially the length of rivers and dendritic streams) and land use (especially forest regions) in the wet season. Our research provides a new perspective of community assembly in rivers and important insights into future research on environmental monitoring and classified management of aquatic ecosystems under the influence of human activity.

Characterization of air pollutant emissions from construction machinery in Beijing and evaluation of the effectiveness of control measures based on information code registration data.

Non-road mobile machinery (NRMM), mainly construction machinery, has a high emission intensity of air pollutants, significantly impacting urban air quality. Most previous estimates of NRMM emissions have employed a top-down approach mainly based on estimates of energy consumption, leading to large uncertainties. This study uses the information code registration data specified in the latest regulations to establish a bottom-up method for emission accounting to more precisely identify the characteristics of air pollutant emissions from construction machinery in Beijing in 2020. Moreover, the study evaluates the effectiveness of the implementation of the corresponding control measures in conjunction with the current situation of pollution control of NRMM in Beijing. The results show the following: (1) Based on the information code registration data, there are 37,000-based fuel construction machines, with excavators accounting for the largest proportion (56%), loaders and forklifts also accounting for large proportions (19% and 15%, respectively), representing the main types of construction machinery. (2) Information code registration data better reflect the actual situation of construction machinery emissions than the top-down method; the emissions of the main air pollutants NOx, PM2.5, and VOCs amount to 12,000 tons, 600 tons, and 1000 tons, respectively, which are overestimated to some extent by the top-down method. (3) Loaders and excavators have a large contribution to emissions, accounting for 80-91% of these three pollutants emissions; there is a large quantity of machinery classified into the China III standard, accounting for 64-68% of these pollutants emissions; the designation of low emission zones banning the use of high-emission machinery plays a positive role in pollution reduction, but high-emission machinery is still used in these regions, which requires further attention. (4) In the future, the scope of these regions banning high-emission machinery and the types of controlled machinery should be further expanded, and the supervision and enforcement should be strengthened, Furthermore, the structural adjustment and energy conservation of construction machinery should be promoted, and measures such as electrification should be implemented for part of the light construction machinery to continue to reduce pollutant emissions.

Ten-year emission characteristics of atmospheric pollutants from incineration of sacrificial offerings in China.

The incineration of sacrificial offerings is a significant widely practiced custom that is also a kind of neglected air pollution source in China. Our results showed that the emission factors of particulate matter, SO2, CO, NOx, and VOCs emitted from the incineration of sacrificial offerings with purification systems were reduced by 95%, 19%, 9%, 82%, and 42%, respectively, compared with those without a purification system, revealing a significant effect of the flue gas purification system on reducing particulate matter and gaseous pollutants. The emission level of air pollutants from the incineration of sacrificial offerings remained stable before 2013 and then showed a remarkable decrease after the implementation of China´s Air Pollution Prevention Action Plan in 2013. The emissions of TSP (total suspended particulate), PM10, PM2.5, and NOx in 2009 were 8222, 6106, 5656 and 15,878 ton, respectively, obviously higher than 3434, 2551, 2305 and 8579 ton in 2019. Such trend was affected by both the quantity of incineration and the installation rate of purification systems after the Emission Standard of Air Pollutants for Crematory (GB 13801-2015) issued in China. Distinct spatial distribution of atmospheric pollutants from incineration of sacrificial offerings was found with higher in the east and south of China than the west and north of China, which is proportional to the regional economy and population. The maximum ground-level concentration typically occurred at 0.12-0.2 km from the pollution source, posing potential health risks to people entering and exiting funeral and burial sites and nearby residents.

A comprehensive emission inventory of hazardous air pollutants from municipal solid waste incineration in China.

The Hazardous air pollutants (HAPs) released from increasing municipal solid waste incineration (MSWI) plants have drawn great concerns in China. However, a full picture of their emission characteristics is still urgently needed, especially after the implementation of stricter emission limits on MSWI. In this study, a comprehensive historical emission inventory of HAPs emitted from MSWI plants in China during the period of 2006-2017 was dedicatedly established by integrating with detailed plant-level activity data and renewed localized emission factors. Overall, HAPs emissions initially increased with years, then peaked or slowed increase in the year 2014, but leveled off after 2016 due to the gradually and fully implementing of newly revised national emission standard (GB18485-2014) applied to mainland China and much stricter local standards for several provinces and cities. It was estimated that totally 50,716 tons (t) of NOx, 13,026 t of CO, 7988 t of SO2, 4399 t of PM, 1943 t of HCl, 9916 kg of Pb, 5901 kg of Mn, 4805 kg of Cu, 3574 kg of Cr, 3329 kg of Ni, 2154 kg of Hg, 1168 kg of Cd, 862 kg of As, 409 kg of Co, 216 kg of Sb, 13 kg of Tl, and 19 g toxic equivalent quantity of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans were emitted from 337 MSWI plants scattered in 30 provinces of mainland China in 2017, respectively. HAPs emissions were heavily concentrated in developed coastal provinces and cities. Scenario analysis highlighted the importance of continuous improvement and upgrade on advanced air pollution control devices and MSWI management to meet the future ultra-low emission limits and minimize the harmful impacts of HAPs on atmospheric environment and public health.

Quantitative of instantaneous BC emissions based on vehicle specific power from real-world driving diesel trucks in China.

In-depth exploration of the potential links between instantaneous black carbon (BC) emissions and driving parameters from real-world diesel trucks (DTs) is a key step toward development of a highly flexible vehicle emissions estimation system. In this study, we conducted real-world measurements on 22 DTs with mainstream types and emission standards, and obtained instantaneous data of BC emissions and vehicle driving. Since vehicle specific power (VSP) is an excellent surrogate for engine load, we characterize the instantaneous BC emissions and VSP distributions, and then establish links between VSP and fuel consumption, VSP and BC emission rates, VSP and BC emission factors (EFs), respectively. We find that BC emission rates of China V light-duty DTs installed with diesel particulate filter (DPF) are significantly lower (2 to 3 orders of magnitude) than those with China III and China IV. Frequent acceleration and deceleration of vehicles maybe the main reason leads to high BC emissions. The distribution of VSP is mainly concentrated in the ranges of -30 to 35 kW/t in the scope of this study. We find that VSP and BC EFs did not show a consistent pattern for all tested DTs, and BC EFs present obvious fluctuations with the VSP variation. The average fuel-based BC EFs vary by factors of 2.27-8.25 from the lowest to highest EFs. Through a fitting of the third-order polynomial function, we finally quantify and provide fitting formulas of BC EFs and VSP under more detailed categorization. Our results can provide important data support for accurate quantification of BC EFs, and even emission inventory calculations.