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第二十四届大气污染防治技术研讨会

作者： Xionghui Qiu Shuxiao Wang Qi Ying Lei Duan Jia Xing Jingyuan Cao Di Wu Xiaoxiao Li Chengzhi Xing Xiao Yan Cheng Liu Jiming Hao MOE Key Laboratory of Resources and Environmental System Optimization College of Environmental Science and Engineering North China Electric Power University State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Zachry Department of Civil Engineering Texas A&M University College Station School of Earth and Space Sciences University of Science and Technology of China National Engineering Research Center of Urban Environmental Pollution Control Beijing Municipal Research Institute of Environmental Protection Department of Precision Machinery and Precision Instrumentation University of Science and Technology of China

Atmospheric glyoxal(GLY) and methylglyoxal(MGLY) are key precursors of secondary organic aerosol(SOA). However, anthropogenic emissions of GLY and MGLY and their contribution to surface GLY and MGLY concentrations, as well as the secondary organic aerosol(SOA) formation, are not well quantified. By developing an emission inventory of anthropogenic GLY and MGLY and improving Community Multiscale Air Quality Model(CMAQ) with SOA formation from irreversible surface uptake of GLY and MGLY, as well as a precursor-origin resolved technique, we quantified the source contributions of GLY and MGLY and their impact on wintertime SOA formation in Beijing, China. The total emissions of GLY and MGLY in Beijing in 2017 are 1.1×10～4 kmol and 7.0×10～3 kmol, respectively. Anthropogenic primary emissions are found to be the dominant contributor to GLY and MGLY concentrations(～74% for GLY and ～63% for MGLY). Anthropogenic primary emissions of GLY and MGLY contributes to 30% of GLY/MGLY SOA daily average concentration and accounts for up to 45% of nighttime GLY/MGLY SOA. The study suggests that the anthropogenic GLY and MGLY emissions, mainly from gasoline vehicles and cooking, are important for SOA formation and shall be strictly controlled in Chinese megacities.

关键词： SOA Sources of atmospheric glyoxal and methylglyoxal in Beijing and its impact on wintertime secondary organic aerosol formation

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Global Future Population Exposure to Heatwaves

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SSRN 2023年

作者： Wang, Yuwei Zhao, Na Yin, Xiaozhe Wu, Chaoyang Chen, Mingxing Jiao, Yimeng Yue, Tianxiang State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing100101 China Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application Nanjing210023 China University of Southern California United States Key Laboratory of Land Surface Pattern and Simulation Institute Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China Key Laboratory of Regional Sustainable Development Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China

The increasing exposure to extreme heatwaves in urban areas from both climate change and the urban heat island (UHI) effect is posing multiple threats and challenges to human society. Despite a growing number of studies focusing on extreme exposure, research advances are still limited in some aspects like oversimplifies of some inter-individual factors of human exposure, resulting in unreliable and unrealistic estimates of future results. In addition, little research performed comprehensive and fine-resolution global analysis in future scenarios. In this study, we present the first global fine-resolution projection of future changing urban population exposure to heatwaves by 2100 under four shared socioeconomic pathways (SSPs) by considering the urban development at global, regional, and national scales. Overall, global urban population exposure to heatwaves is rising under the four SSPs. Temperate and tropical zones predictably have the greatest exposure among all climate zones. Coastal cities are projected to have the greatest exposure, followed closely by cities at low altitudes. Middle-income countries have the lowest exposure and the lowest inequality of exposure among countries. Individual climate effects contributed the most (about 46.4%) to future changes in exposure, followed by the interactive effect between climate and urbanization (about 18.5%). Our results indicate that more attention needs to be paid to policy improvements and sustainable development planning of global coastal cities and some low-altitude cities, especially in low- and high-income countries. Meanwhile, this study also highlights the impact of continued future urban expansion on population exposure to heatwaves. © 2023, The Authors. All rights reserved.

关键词： Climate change

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Global Future Population Exposure to Heatwaves

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SSRN 2023年

关键词： Climate change

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Global Future Population Exposure to Heatwaves

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SSRN 2023年

关键词： Climate change

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气候变化情景下中国因高温造成的劳动生产力损失预估

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Science Bulletin 2023年第22期68卷 2827-2837,M0006页

作者：程亮亮谷魁英赵亮王会滨纪思翰刘钊黄建斌陈艺丹高学杰徐影王灿罗勇蔡闻佳宫鹏梁万年黄存瑞 School of Public Health Sun Yat-sen UniversityGuangzhou 510080China Vanke School of Public Health Tsinghua UniversityBeijing 100084China State Key Laboratory of Numerical Modelling for Atmosphere Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China School of Linkong Economics and Management Beijing Institute of Economics and ManagementBeijing 100102China Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100190China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100084China Climate Change Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China National Climate Centre China Meteorological AdministrationBeijing 100081China Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China Department of Earth Sciences and Department of Geography University of Hong KongHong Kong 999077China Institute of Healthy Chin1 Tsinghua UniversityBeijing 100084China

气候变化背景下,高温会影响职业人群的工作效率并造成劳动生产力损失.本研究基于区域气候模式并采用本土化的暴露-反应函数,预估了未来气候变化情景下中国因高温造成的劳动时间损失.研究发现,与基线期的213亿小时高温相关劳动时间损失相... 详细信息

气候变化背景下,高温会影响职业人群的工作效率并造成劳动生产力损失.本研究基于区域气候模式并采用本土化的暴露-反应函数,预估了未来气候变化情景下中国因高温造成的劳动时间损失.研究发现,与基线期的213亿小时高温相关劳动时间损失相比,到21世纪末在RCP2.6、RCP4.5和RCP8.5情景下,损失将分别增加-17.8%、10.8%及121.1%.损失主要集中在华南、华中和华东地区,其中广东与河南将占到全国总损失的四分之一.因为这些区域的温度将更高、人口更密集、户外工作者在总人群中的比例较大.与RCP2.6、RCP4.5和RCP8.5情景相比,若能实现1.5℃温控目标,将分别能够避免11.8%、33.7%和53.9%的劳动时间损失,相当于避免了全中国21世纪中叶的0.1%、0.6%及1.4%的年均GDP损失.本研究显示未来气候变化会给中国造成严重的热相关劳动生产力损失,并强调亟需采取因地制宜的气候减缓及适应策略以保护职业人群健康.本研究对其他与中国相似的发展中国家同样具有重要意义.

关键词： Climate change Heat stress Labor Work hours lost Occupational health

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Vertical Transport of Ultrafine Particles and Turbulence Evolution Impact on New Particle Formation at the Surface & Canton Tower

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SSRN 2023年

作者： Wu, Hao Li, Zhanqing Hai, Shangfei Gao, Yang Jiang, Jingkun Zhao, Bin Cribb, Maureen Zhang, Dongmei Pu, Dongyang Liu, Mengqi Wang, Chunling Lan, Jing Wang, Yuying Key Laboratory of China Meteorological Administration Atmospheric Sounding School of Electrical Engineering Chengdu University of Information Technology Chengdu610225 China Department of Atmospheric and Oceanic Science University of Maryland College ParkMD20742 United States College of Oceanic and Atmospheric Sciences Ocean University of China Qingdao266100 China Frontiers Science Center for Deep Ocean Multispheres and Earth System Key Laboratory of Marine Environmental Science and Ecology Ministry of Education Ocean University of China Qingdao266100 China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing100084 China College of Global Change and Earth System Science Beijing Normal University Beijing100875 China Guangzhou Climate and Agrometeorology Center Guangzhou511430 China Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration Nanjing University of Information Science & Technology Nanjing210044 China

New particle formation (NPF) is a key process occurring in the planetary boundary layer (PBL). Newly formed particles are an important source of aerosols and cloud condensation nuclei (CCN) that influence clouds and climate, while the distribution of these new particles at different altitudes has rarely been studied. In-situ measurements of ultrafine particles (UFP) observed at the ground and at the top of the Canton Tower (454 m) located in downtown Guangzhou in southern China were analyzed using the measurements of multiple meteorological and physicochemical quantities, as both observed during a field campaign and simulated with the WRF-chem model. We found that turbulence and NPF characters vary considerably with heights, with UFP concentration diminishing by half from the surface to the tower top. This indicates the UFP transports upward from the ground in the lower boundary layer. A consistent relationship is established between the occurrences of NPF and the evolution of turbulence. The correlation between the exchange ratio at the tower top has correlated well with nucleation growth, suggesting that turbulence can play an important role in the episodes of NPF growth, whose growth rate is closely related to the turbulence exchange ratio, effectively dictating the ultrafine particle concentration before and during the lockdown period. A new mechanism is thus hypothesized: NPF happens eailer near the surface and grows faster at the upper PBL, attributed to condensable vapors being transported by turbulent vertical mixing in the boundary layer. Model simulations using the WRF-Chem model reveal that the exchange ratio changed the NPF parameters, supporting the proposed mechanism that the evolution of the PBL variation has a significant impact on NPF, which should not be omitted in the NPF research, since this physical factor could be a dominant one in the NPF mechanism. © 2023, The Authors. All rights reserved.

关键词： Turbulence

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Method for constructing multi-dimensional feature map of malicious code

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Journal of Physics: Conference Series 2021年第4期1748卷

作者： Haocong Ma Ji Zhang Junhua Zhou Xiang Zhai Junjie Xue Hang Ji State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing 100854 China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing simulation Center Beijing 100854 China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing 100854 China School of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China

Malicious code is characterized by a large number of types, rapid increase in number, continuous update of transmission routes, and continuous enhancement of back analysis and back detection methods. Therefore, how to effectively detect and analyze malicious code has been a problem of great concern. This paper studies the features of binary file and disassembly file of malicious code, introduces the concept of information gain, and proposes a method to construct the multi-dimensional characteristic graph of malicious code. Finally, the convolutional neural network is used to classify the multi-dimensional feature graph of malicious code, which provides a new idea for the feature extraction of malicious code.

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Estimation of pregnancy losses attributable to exposure to ambient fine particles in south Asia: an epidemiological case-control study

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The Lancet Planetary Health 2021年第1期5卷 e15-e24页

作者： Xue, Tao Guan, Tianjia Geng, Guannan Zhang, Qiang Zhao, Yong Zhu, Tong Institute of Reproductive and Child Health Ministry of Health Key Laboratory of Reproductive Health Peking University Beijing China Department of Epidemiology and Biostatistics School of Public Health Peking University Beijing China School of Public Health Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Tsinghua University Beijing China College of Liberal Arts and Sciences University of Connecticut Storrs CT United States BIC-ESAT and SKL-ESPC College of Environmental Science and Engineering Peking University Beijing China

Background: Maternal exposure to ambient particulate matter (PM2·5) is associated with pregnancy loss (ie, stillbirth and miscarriage). South Asia has the highest burden of pregnancy loss globally and is one of t...

Background: Maternal exposure to ambient particulate matter (PM_2·5) is associated with pregnancy loss (ie, stillbirth and miscarriage). South Asia has the highest burden of pregnancy loss globally and is one of the most PM_2·5 polluted regions in the world. However, knowledge of the relevant exposure–response function for mothers is insufficient. Methods: In this epidemiological case-control study, we collected data from Demographic and Health Surveys from India, Pakistan, and Bangladesh for the period 1998–2016 for women who reported at least one pregnancy loss and one or more livebirths. We assessed ambient exposure during gestation with satellite-based PM_2·5 measurements for the period. To derive the exposure–response function, we did a self-compared case-control study in which each case of pregnancy loss was compared with a successful livebirth control or controls by the same mother. Using the estimated exposure–response function, we quantified pregnancy losses attributable to PM_2·5 in the region for the period 2000–16 using a standard risk assessment approach. Findings: We assessed data for 34 197 mothers, who had at least one pregnancy loss and one or more livebirth, of whom 26 282 (76·9%) were from India, 4228 (12·4%) were from Pakistan, and 3687 (10·8%) were from Bangladesh. The 34 197 cases of pregnancy loss were matched with 76 282 livebirth controls. The mean level of PM_2·5 exposure was 56·00 μg/m³ (SD 30·82) for cases and 54·57 μg/m³ (31·73) for controls. After adjustment for maternal age, non-linear terms for temperature and humidity, seasonal variation, and long-term trends, each 10 μg/m³ increment in PM_2·5 was associated with an odds ratio for pregnancy loss of 1·03 (95% CI 1·02–1·05). According to the estimated non-linear exposure–response function by age and urban residence versus rural residence, for the period 2000–16, an estimated 349 681 (95% CI 152

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Global Future Population Exposure to Heatwaves

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SSRN 2023年

作者： Wang, Yuwei Zhao, Na Yin, Xiaozhe Wu, Chaoyang Chen, Mingxing Jiao, Yimeng Yue, Tianxiang State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing100101 China Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application Nanjing210023 China Department of Environmental Health Harvard T.H. Chan School of Public Health BostonMA United States Key Laboratory of Land Surface Pattern and Simulation Institute Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China Key Laboratory of Regional Sustainable Development Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China

关键词： Climate change

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Large-Scale Single Tree Information Extraction of Oil Palm in Malaysia Based on Sub-Meter Visible Light Satellite Images

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SSRN 2024年

作者： Zhang, Sen Li, Nan Cui, Yaoping Dong, Jinwei Yu, Le Ran, Lishan Chen, Ziyue Niu, Jiqiang Yan, Wei Kanniah, Kasturi Devi Xiao, Xiangming Zhang, Yongguang Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions Henan University Ministry of Education Kaifeng475004 China College of Geography and Environmental Science Henan University Kaifeng475004 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application International Institute for Earth System Sciences Nanjing University Nanjing210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China Department of Earth System Science Ministry of Education Key Laboratory for Earth System Modeling Institute for Global Change Studies Tsinghua University Beijing100084 China Department of Geography The University of Hong Kong Pokfulam999077 Hong Kong State Key Laboratory of Earth Surface Processes and Resource Ecology College of Global Change and Earth System Science Beijing Normal University Beijing100875 China College of Geographic Sciences Xinyang Normal University Xinyang464000 China Department of Geoinformation Faculty of Built Environment & Surveying Universiti Teknologi Malaysia Johor Bahru81310 Malaysia Department of Microbiology and Plant Biology Center for Spatial Analysis University of Oklahoma NormanOK73019 United States College of Environment and Planning Faculty of Geoinformation and Real Estate

The distribution of specific tree species and single tree information can shift down the research scale of geography and ecology, bridging research from regional to local scales. However, efficiently and finely extracting the spatial distribution and single tree information for a tree species regionally has always been a challenge due to the constraints of data and algorithms. With sub-meter visible light satellite images (RGB bands) in 2021 to 2022, we constructed a novel method for extracting the spatial distribution and single tree information of oil palm across Malaysia, namely the Single Tree Extraction Method - Oil Palm (STEM-OP). We developed a graphic morphological algorithm based on gradient difference window detection to extract the spatial distribution of oil palms. Then, we proposed an algorithm of double ring sliding detection algorithm to identify the canopy texture features of single oil palm. Finally, an adaptive iterative erosion algorithm was employed to separate overlapping and adjacent canopies into single trees. The overall accuracy of both the spatial distribution and number of single oil palm extracted by STEM-OP exceeded 90%. Our study revealed that the total area of oil palm in Malaysia was 5.25 million hectares, with a total of 572.6 million trees and an average planting density of 109 palms per hectare. The STEM-OP addresses the computational inefficiencies of methods with training samples and limitations of satellite image bands. For the first time, our study extracts the refined spatial distribution of oil palm and obtains the planting density and single tree position on a national scale. All of these are of great value to the formulation of oil palm development policies and ecological protection measures. © 2024, The Authors. All rights reserved.

关键词： Morphology

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