Articles | Volume 16, issue 5
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Typhoon-associated air quality over the Guangdong–Hong Kong–Macao Greater Bay Area, China: machine-learning-based prediction and assessment
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, China
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, China
Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China
No articles found.
Yuan Wang, Qiangqiang Yuan, Tongwen Li, Yuanjian Yang, Siqin Zhou, and Liangpei Zhang
Earth Syst. Sci. Data, 15, 3597–3622,Short summary
We propose a novel spatiotemporally self-supervised fusion method to establish long-term daily seamless global XCO2 and XCH4 products. Results show that the proposed method achieves a satisfactory accuracy that distinctly exceeds that of CAMS-EGG4 and is superior or close to those of GOSAT and OCO-2. In particular, our fusion method can effectively correct the large biases in CAMS-EGG4 due to the issues from assimilation data, such as the unadjusted anthropogenic emission for COVID-19.
Zhiheng Liao, Meng Gao, Jinqiang Zhang, Jiaren Sun, Jiannong Quan, Xingcan Jia, Yubing Pan, and Shaojia Fan
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).Short summary
This study collected 1,897 ozonesondes from two Chinese megacities (Beijing and Hong Kong) in 2000–2022 to investigate climatological vertical heterogeneity of lower-tropospheric ozone distribution with a mixing-layer-height-referenced (h-referenced) vertical coordinate system. This vertical coordinate system highlighted O3 stratification features existing at the mixing layer–free troposphere interface and provided a better understanding of O3 pollution in urban regions.
Lei Kong, Xiao Tang, Jiang Zhu, Zifa Wang, Yele Sun, Pingqing Fu, Meng Gao, Huangjian Wu, Miaomiao Lu, Qian Wu, Shuyuan Huang, Wenxuan Sui, Jie Li, Xiaole Pan, Lin Wu, Hajime Akimoto, and Gregory R. Carmichael
Atmos. Chem. Phys., 23, 6217–6240,Short summary
A multi-air-pollutant inversion system has been developed in this study to estimate emission changes in China during COVID-19 lockdown. The results demonstrate that the lockdown is largely a nationwide road traffic control measure with NOx emissions decreasing by ~40 %. Emissions of other species only decreased by ~10 % due to smaller effects of lockdown on other sectors. Assessment results further indicate that the lockdown only had limited effects on the control of PM2.5 and O3 in China.
Peng Wang, Ruhan Zhang, Shida Sun, Meng Gao, Bo Zheng, Dan Zhang, Yanli Zhang, Gregory R. Carmichael, and Hongliang Zhang
Atmos. Chem. Phys., 23, 2983–2996,Short summary
In China, the number of vehicles has jumped significantly in the last decade. This caused severe traffic congestion and aggravated air pollution. In this study, we developed a new temporal allocation approach to quantify the impacts of traffic congestion. We found that traffic congestion worsens air quality and the health burden across China, especially in the urban clusters. More effective and comprehensive vehicle emission control policies should be implemented to improve air quality in China.
Hui Zhang, Ming Luo, Yongquan Zhao, Lijie Lin, Erjia Ge, Yuanjian Yang, Guicai Ning, Jing Cong, Zhaoliang Zeng, Ke Gui, Jing Li, Ting On Chan, Xiang Li, Sijia Wu, Peng Wang, and Xiaoyu Wang
Earth Syst. Sci. Data, 15, 359–381,Short summary
We generate the first monthly high-resolution (1 km) human thermal index collection (HiTIC-Monthly) in China over 2003–2020, in which 12 human-perceived temperature indices are generated by LightGBM. The HiTIC-Monthly dataset has a high accuracy (R2 = 0.996, RMSE = 0.693 °C, MAE = 0.512 °C) and describes explicit spatial variations for fine-scale studies. It is freely available at https://zenodo.org/record/6895533 and https://data.tpdc.ac.cn/disallow/036e67b7-7a3a-4229-956f-40b8cd11871d.
Haolin Wang, Xiao Lu, Daniel J. Jacob, Owen R. Cooper, Kai-Lan Chang, Ke Li, Meng Gao, Yiming Liu, Bosi Sheng, Kai Wu, Tongwen Wu, Jie Zhang, Bastien Sauvage, Philippe Nédélec, Romain Blot, and Shaojia Fan
Atmos. Chem. Phys., 22, 13753–13782,Short summary
We report significant global tropospheric ozone increases in 1995–2017 based on extensive aircraft and ozonesonde observations. Using GEOS-Chem (Goddard Earth Observing System chemistry model) multi-decadal global simulations, we find that changes in global anthropogenic emissions, in particular the rapid increases in aircraft emissions, contribute significantly to the increases in tropospheric ozone and resulting radiative impact.
Fan Wang, Gregory R. Carmichael, Jing Wang, Bin Chen, Bo Huang, Yuguo Li, Yuanjian Yang, and Meng Gao
Atmos. Chem. Phys., 22, 13341–13353,Short summary
Unprecedented urbanization in China has led to serious urban heat island (UHI) issues, exerting intense heat stress on urban residents. We find diverse influences of aerosol pollution on urban heat island intensity (UHII) under different circulations. Our results also highlight the role of black carbon in aggravating UHI, especially during nighttime. It could thus be targeted for cooperative management of heat islands and aerosol pollution.
Zexia Duan, Zhiqiu Gao, Qing Xu, Shaohui Zhou, Kai Qin, and Yuanjian Yang
Earth Syst. Sci. Data, 14, 4153–4169,Short summary
Land–atmosphere interactions over the Yangtze River Delta (YRD) in China are becoming more varied and complex, as the area is experiencing rapid land use changes. In this paper, we describe a dataset of microclimate and eddy covariance variables at four sites in the YRD. This dataset has potential use cases in multiple research fields, such as boundary layer parametrization schemes, evaluation of remote sensing algorithms, and development of climate models in typical East Asian monsoon regions.
Bo Li, Cheng Liu, Qihou Hu, Mingzhai Sun, Chengxin Zhang, Shulin Zhang, Yizhi Zhu, Ting Liu, Yike Guo, Gregory R. Carmichael, and Meng Gao
Preprint archivedShort summary
Ambient particles have an important impact on human health, meteorology and climate change. By building a deep spatiotemporal neural network model we have overcome the long-standing limitations and get the full time and space coverage ground PM2.5 concentrations. We open the neural network black box data model by using sensitivity analysis and visualization techniques. This research will help improve health effects studies, climate effects of aerosols, and air quality prediction.
Chenhong Zhou, Fan Wang, Yike Guo, Cheng Liu, Dongsheng Ji, Yuesi Wang, Xiaobin Xu, Xiao Lu, Yan Wang, Gregory Carmichael, and Meng Gao
Earth Syst. Sci. Data Discuss.,
Manuscript not accepted for further reviewShort summary
We develop an eXtreme Gradient Boosting (XGBoost) model integrating high-resolution meteorological data, satellite retrievals of trace gases, etc. to provide reconstructed daily ground-level O3 over 2005–2021 in China. It can facilitate climatological, ecological, and health research. The dataset is freely available at Zenodo (https://zenodo.org/record/6507706#.Yo8hKujP13g; Zhou, 2022).
Lian Zong, Yuanjian Yang, Haiyun Xia, Meng Gao, Zhaobin Sun, Zuofang Zheng, Xianxiang Li, Guicai Ning, Yubin Li, and Simone Lolli
Atmos. Chem. Phys., 22, 6523–6538,Short summary
Heatwaves (HWs) paired with higher ozone (O3) concentration at surface level pose a serious threat to human health. Taking Beijing as an example, three unfavorable synoptic weather patterns were identified to dominate the compound HW and O3 pollution events. Under the synergistic stress of HWs and O3 pollution, public mortality risk increased, and synoptic patterns and urbanization enhanced the compound risk of events in Beijing by 33.09 % and 18.95 %, respectively.
Shaohui Zhou, Yuanjian Yang, Zhiqiu Gao, Xingya Xi, Zexia Duan, and Yubin Li
Atmos. Meas. Tech., 15, 757–773,Short summary
Our research has determined the possible relationship between Weibull natural wind mesoscale parameter c and shape factor k with height under the conditions of a desert steppe terrain in northern China, which has great potential in wind power generation. We have gained an enhanced understanding of the seasonal changes in the surface roughness of the desert grassland and the changes in the incoming wind direction.
Shihan Chen, Yuanjian Yang, Fei Deng, Yanhao Zhang, Duanyang Liu, Chao Liu, and Zhiqiu Gao
Atmos. Meas. Tech., 15, 735–756,Short summary
This paper proposes a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a random forest (RF) model. The spatial distribution of CUHII was evaluated at 30 m resolution based on the output of the RF model. The present RF model framework for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII.
Xinyan Li, Yuanjian Yang, Jiaqin Mi, Xueyan Bi, You Zhao, Zehao Huang, Chao Liu, Lian Zong, and Wanju Li
Atmos. Meas. Tech., 14, 7007–7023,Short summary
A random forest (RF) model framework for Fengyun-4A (FY-4A) daytime and nighttime quantitative precipitation estimation (QPE) is established using FY-4A multi-band spectral information, cloud parameters, high-density precipitation observations and physical quantities from reanalysis data. The RF model of FY-4A QPE has a high accuracy in estimating precipitation at the heavy-rain level or below, which has advantages for quantitative estimation of summer precipitation over East Asia in future.
Chengzhi Xing, Cheng Liu, Hongyu Wu, Jinan Lin, Fan Wang, Shuntian Wang, and Meng Gao
Earth Syst. Sci. Data, 13, 4897–4912,Short summary
Observations of atmospheric composition, especially vertical profile observations, remain sparse and rare on the Tibetan Plateau (TP), due to extremely high altitude, topographical heterogeneity and the grinding environment. This paper introduces a high-time-resolution (~ 15 min) vertical profile observational dataset of atmospheric composition (aerosols, NO2, HCHO and HONO) on the TP for more than 1 year (2017–2019) using a passive remote sensing technique.
Meng Gao, Yang Yang, Hong Liao, Bin Zhu, Yuxuan Zhang, Zirui Liu, Xiao Lu, Chen Wang, Qiming Zhou, Yuesi Wang, Qiang Zhang, Gregory R. Carmichael, and Jianlin Hu
Atmos. Chem. Phys., 21, 11405–11421,Short summary
Light absorption and radiative forcing of black carbon (BC) is influenced by both BC itself and its interactions with other aerosol chemical compositions. In this study, we used the online coupled WRF-Chem model to examine how emission control measures during the Asian-Pacific Economic Cooperation (APEC) conference affect the mixing state and light absorption of BC and the associated implications for BC-PBL interactions.
Lian Zong, Yuanjian Yang, Meng Gao, Hong Wang, Peng Wang, Hongliang Zhang, Linlin Wang, Guicai Ning, Chao Liu, Yubin Li, and Zhiqiu Gao
Atmos. Chem. Phys., 21, 9105–9124,Short summary
In recent years, summer O3 pollution over eastern China has become more serious, and it is even the case that surface O3 and PM2.5 pollution can co-occur. However, the synoptic weather pattern (SWP) related to this compound pollution remains unclear. Regional PM2.5 and O3 compound pollution is characterized by various SWPs with different dominant factors. Our findings provide insights into the regional co-occurring high PM2.5 and O3 levels via the effects of certain meteorological factors.
Yan Zhang, Yu Zhao, Meng Gao, Xin Bo, and Chris P. Nielsen
Atmos. Chem. Phys., 21, 6411–6430,Short summary
We combined air quality and exposure response models to analyze the benefits for air quality and human health of China’s ultra-low emission policy in one of its most developed regions. Atmospheric observations and the air quality model were also used to demonstrate improvement of emission inventories incorporating online emission monitoring data. With implementation of the policy in both power and industrial sectors, the attributable deaths due to PM2.5 exposure are estimated to decrease 5.5 %.
Peter Sherman, Meng Gao, Shaojie Song, Alex T. Archibald, Nathan Luke Abraham, Jean-François Lamarque, Drew Shindell, Gregory Faluvegi, and Michael B. McElroy
Atmos. Chem. Phys., 21, 3593–3605,Short summary
The aims here are to assess the role of aerosols in India's monsoon precipitation and to determine the relative contributions from Chinese and Indian emissions using CMIP6 models. We find that increased sulfur emissions reduce precipitation, which is primarily dynamically driven due to spatial shifts in convection over the region. A significant increase in precipitation (up to ~ 20 %) is found only when both Indian and Chinese sulfate emissions are regulated.
Shaojie Song, Tao Ma, Yuzhong Zhang, Lu Shen, Pengfei Liu, Ke Li, Shixian Zhai, Haotian Zheng, Meng Gao, Jonathan M. Moch, Fengkui Duan, Kebin He, and Michael B. McElroy
Atmos. Chem. Phys., 21, 457–481,Short summary
We simulate the atmospheric chemical processes of an important sulfur-containing organic aerosol species, which is produced by the reaction between sulfur dioxide and formaldehyde. We can predict its distribution on a global scale. We find it is particularly rich in East Asia. This aerosol species is more abundant in the colder season partly because of weaker sunlight.
Ziqiang Ma, Jintao Xu, Siyu Zhu, Jun Yang, Guoqiang Tang, Yuanjian Yang, Zhou Shi, and Yang Hong
Earth Syst. Sci. Data, 12, 1525–1544,Short summary
Focusing on the potential drawbacks in generating the state-of-the-art IMERG data in both the TRMM and GPM era, a new daily calibration algorithm on IMERG was proposed, as well as a new AIMERG precipitation dataset (0.1°/half-hourly, 2000–2015, Asia) with better quality than IMERG for Asian scientific research and applications. The proposed daily calibration algorithm for GPM is promising and applicable in generating the future IMERG in either an operational scheme or a retrospective manner.
Pablo E. Saide, Meng Gao, Zifeng Lu, Daniel L. Goldberg, David G. Streets, Jung-Hun Woo, Andreas Beyersdorf, Chelsea A. Corr, Kenneth L. Thornhill, Bruce Anderson, Johnathan W. Hair, Amin R. Nehrir, Glenn S. Diskin, Jose L. Jimenez, Benjamin A. Nault, Pedro Campuzano-Jost, Jack Dibb, Eric Heim, Kara D. Lamb, Joshua P. Schwarz, Anne E. Perring, Jhoon Kim, Myungje Choi, Brent Holben, Gabriele Pfister, Alma Hodzic, Gregory R. Carmichael, Louisa Emmons, and James H. Crawford
Atmos. Chem. Phys., 20, 6455–6478,Short summary
Air quality forecasts over the Korean Peninsula captured aerosol optical depth but largely overpredicted surface PM during a Chinese haze transport event. Model deficiency was related to the calculation of optical properties. In order to improve it, aerosol size representation needs to be refined in the calculations, and the representation of aerosol properties, such as size distribution, chemical composition, refractive index, hygroscopicity parameter, and density, needs to be improved.
Meng Gao, Jinhui Gao, Bin Zhu, Rajesh Kumar, Xiao Lu, Shaojie Song, Yuzhong Zhang, Beixi Jia, Peng Wang, Gufran Beig, Jianlin Hu, Qi Ying, Hongliang Zhang, Peter Sherman, and Michael B. McElroy
Atmos. Chem. Phys., 20, 4399–4414,Short summary
A regional fully coupled meteorology–chemistry model, Weather Research and Forecasting model with Chemistry (WRF-Chem), was employed to study the seasonality of ozone (O3) pollution and its sources in both China and India.
Zhining Tao, Mian Chin, Meng Gao, Tom Kucsera, Dongchul Kim, Huisheng Bian, Jun-ichi Kurokawa, Yuesi Wang, Zirui Liu, Gregory R. Carmichael, Zifa Wang, and Hajime Akimoto
Atmos. Chem. Phys., 20, 2319–2339,Short summary
One goal of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III is to identify strengths and weaknesses of current air quality models to provide insights into reducing uncertainties. This study identified that a 15 km grid would be the optimal horizontal resolution in terms of performance and resource usage to capture average and extreme air quality over East Asia and is thus suggested for use in future MICS-Asia modeling activities if the investigation domain remains the same.
Meng Gao, Zirui Liu, Bo Zheng, Dongsheng Ji, Peter Sherman, Shaojie Song, Jinyuan Xin, Cheng Liu, Yuesi Wang, Qiang Zhang, Jia Xing, Jingkun Jiang, Zifa Wang, Gregory R. Carmichael, and Michael B. McElroy
Atmos. Chem. Phys., 20, 1497–1505,Short summary
We quantified the relative influences of anthropogenic emissions and meteorological conditions on PM2.5 concentrations in Beijing over the winters of 2002–2016. Meteorological conditions over the study period would have led to an increase of haze in Beijing, but the strict emission control measures have suppressed the unfavorable influences of the recent climate.
Meng Gao, Zhiwei Han, Zhining Tao, Jiawei Li, Jeong-Eon Kang, Kan Huang, Xinyi Dong, Bingliang Zhuang, Shu Li, Baozhu Ge, Qizhong Wu, Hyo-Jung Lee, Cheol-Hee Kim, Joshua S. Fu, Tijian Wang, Mian Chin, Meng Li, Jung-Hun Woo, Qiang Zhang, Yafang Cheng, Zifa Wang, and Gregory R. Carmichael
Atmos. Chem. Phys., 20, 1147–1161,Short summary
Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative feedbacks. This paper discusses the estimates of aerosol radiative forcing, aerosol feedbacks, and possible causes for the differences among the models.
Linlin Wang, Junkai Liu, Zhiqiu Gao, Yubin Li, Meng Huang, Sihui Fan, Xiaoye Zhang, Yuanjian Yang, Shiguang Miao, Han Zou, Yele Sun, Yong Chen, and Ting Yang
Atmos. Chem. Phys., 19, 6949–6967,Short summary
Urban boundary layer (UBL) affects the physical and chemical processes of the pollutants, and UBL structure can also be altered by pollutants. This paper presents the interactions between air pollution and the UBL structure by using the field data mainly collected from a 325 m meteorology tower, as well as from a Doppler wind lidar, during a severe heavy pollution event that occurred during 1–4 December 2016 in Beijing.
Daniel L. Goldberg, Pablo E. Saide, Lok N. Lamsal, Benjamin de Foy, Zifeng Lu, Jung-Hun Woo, Younha Kim, Jinseok Kim, Meng Gao, Gregory Carmichael, and David G. Streets
Atmos. Chem. Phys., 19, 1801–1818,Short summary
Using satellite data, we are able to estimate the emissions of NOx (NOx=NO+NO2), a toxic group of air pollutants, in the Seoul metropolitan area. We first develop an enhanced satellite product that better observes NO2 in urban regions. Using this new product, we derive NOx emissions to be twice as large as the emissions reported by the South Korean government. The implication is that the measures taken to reduce NOx emissions in South Korea have not been as effective as regulators have thought.
Shaojie Song, Meng Gao, Weiqi Xu, Yele Sun, Douglas R. Worsnop, John T. Jayne, Yuzhong Zhang, Lei Zhu, Mei Li, Zhen Zhou, Chunlei Cheng, Yibing Lv, Ying Wang, Wei Peng, Xiaobin Xu, Nan Lin, Yuxuan Wang, Shuxiao Wang, J. William Munger, Daniel J. Jacob, and Michael B. McElroy
Atmos. Chem. Phys., 19, 1357–1371,Short summary
Chemistry responsible for sulfate production in northern China winter haze remains mysterious. We propose a potentially key pathway through the reaction of formaldehyde and sulfur dioxide that has not been accounted for in previous studies. The special atmospheric conditions favor the formation and existence of their complex, hydroxymethanesulfonate (HMS).
Elizabeth M. Lennartson, Jun Wang, Juping Gu, Lorena Castro Garcia, Cui Ge, Meng Gao, Myungje Choi, Pablo E. Saide, Gregory R. Carmichael, Jhoon Kim, and Scott J. Janz
Atmos. Chem. Phys., 18, 15125–15144,Short summary
This paper is among the first to study the diurnal variations of AOD, PM2.5, and their relationships in South Korea. We show that the PM2.5–AOD relationship has strong diurnal variations, and, hence, using AOD data retrieved from geostationary satellite can improve the monitoring of surface PM2.5 air quality on a daily basis as well as constrain the diurnal variation of aerosol emission.
Shaojie Song, Meng Gao, Weiqi Xu, Jingyuan Shao, Guoliang Shi, Shuxiao Wang, Yuxuan Wang, Yele Sun, and Michael B. McElroy
Atmos. Chem. Phys., 18, 7423–7438,Short summary
Severe haze events occur frequently over northern China, especially in winter. Acidity plays a critical role in the formation of secondary PM2.5 and its toxicity. Using field measurements of gases and particles to critically evaluate two thermodynamic models routinely employed to determine particle acidity, we found that China's winter haze particles are generally within a moderately acidic range (pH 4–5) and not highly acidic (0) or neutral (7) as has been previously reported in the literature.
Meng Gao, Zhiwei Han, Zirui Liu, Meng Li, Jinyuan Xin, Zhining Tao, Jiawei Li, Jeong-Eon Kang, Kan Huang, Xinyi Dong, Bingliang Zhuang, Shu Li, Baozhu Ge, Qizhong Wu, Yafang Cheng, Yuesi Wang, Hyo-Jung Lee, Cheol-Hee Kim, Joshua S. Fu, Tijian Wang, Mian Chin, Jung-Hun Woo, Qiang Zhang, Zifa Wang, and Gregory R. Carmichael
Atmos. Chem. Phys., 18, 4859–4884,Short summary
Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative and microphysical feedbacks. A comprehensive overview of the MICS-ASIA III Topic 3 study design is presented.
Xiao Lu, Lin Zhang, Xiong Liu, Meng Gao, Yuanhong Zhao, and Jingyuan Shao
Atmos. Chem. Phys., 18, 3101–3118,Short summary
Deteriorating tropospheric ozone pollution over India may not only affect local human health and vegetation but also perturb global ozone distribution. This study analyzes the processes controlling lower tropospheric ozone over India using OMI satellite observations (2006–2014) and model simulations (1990–2010). We show that the South Asian monsoon largely controls the seasonal cycle and interannual variability of Indian lower tropospheric ozone via changes in ozone production and transport.
Meng Gao, Gregory R. Carmichael, Pablo E. Saide, Zifeng Lu, Man Yu, David G. Streets, and Zifa Wang
Atmos. Chem. Phys., 16, 11837–11851,Short summary
The WRF-Chem model was used to examine how the winter PM2.5 concentrations change in response to changes in emissions and meteorology in North China from 1960 to 2010. The discussions in this study indicate that dramatic changes in emissions are the main cause of increasing haze events in North China, and long-term trends in atmospheric circulations maybe another important cause. We also found aerosol feedbacks have been significantly enhanced from 1960 to 2010, due to higher aerosol loadings.
M. Gao, G. R. Carmichael, Y. Wang, P. E. Saide, M. Yu, J. Xin, Z. Liu, and Z. Wang
Atmos. Chem. Phys., 16, 1673–1691,Short summary
The WRF-Chem model was applied to study the 2010 winter haze in North China. Air pollutants outside Beijing contributed about 64.5 % to the PM2.5 levels in Beijing during this haze event, and most of them are from south Hebei, Tianjin city, Shandong and Henan provinces. In addition, aerosol feedback has important impacts on surface temperature, Relative Humidity (RH) and wind speeds, and these meteorological variables affect aerosol distribution and formation in turn.
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Weixing Hao, Fan Mei, Susanne Hering, Steven Spielman, Beat Schmid, Jason Tomlinson, and Yang Wang
Atmos. Meas. Tech., 16, 3973–3986,Short summary
Airborne aerosol instrumentation plays a crucial role in understanding the spatial distribution of ambient aerosol particles. This study investigates a versatile water-based condensation particle counter through simulations and experiments. It provides valuable insights to improve versatile water-based condensation particle counter (vWCPC) aerosol measurement and operation for the community.
Christina N. Vasilakopoulou, Kalliopi Florou, Christos Kaltsonoudis, Iasonas Stavroulas, Nikolaos Mihalopoulos, and Spyros N. Pandis
Atmos. Meas. Tech., 16, 2837–2850,Short summary
The offline aerosol mass spectrometry technique is a useful tool for the source apportionment of organic aerosol in areas and periods during which an aerosol mass spectrometer is not available. In this work, an improved offline technique was developed and evaluated in an effort to capture most of the partially soluble and insoluble organic aerosol material, reducing the uncertainty of the corresponding source apportionment significantly.
Anton Rusanen, Kristo Hõrrak, Lauri R. Ahonen, Tuomo Nieminen, Pasi P. Aalto, Pasi Kolari, Markku Kulmala, Tuukka Petäjä, and Heikki Junninen
Atmos. Meas. Tech., 16, 2781–2793,Short summary
We present a framework for setting up SMEAR (Station for Measuring Ecosystem–Atmosphere Relations) type measurement station data flows. This framework, called SMEARcore, consists of modular open-source software components that can be chosen to suit various station configurations. The benefits of using this framework are automation of routine operations and real-time monitoring of measurement results.
Najin Kim, Hang Su, Nan Ma, Ulrich Pöschl, and Yafang Cheng
Atmos. Meas. Tech., 16, 2771–2780,Short summary
We propose a multiple-charging correction algorithm for a broad-supersaturation scanning cloud condensation nuclei (BS2-CCN) system which can obtain high time-resolution aerosol hygroscopicity and CCN activity. The correction algorithm aims at deriving the activation fraction's true value for each particle size. The meaningful differences between corrected and original κ values (single hygroscopicity parameter) emphasize the correction algorithm's importance for ambient aerosol measurement.
Lena Francesca Weissert, Geoff Steven Henshaw, David Edward Williams, Brandon Feenstra, Randy Lam, Ashley Collier-Oxandale, Vasileios Papapostolou, and Andrea Polidori
We apply a previously developed remote calibration framework to a network of PM sensors deployed in the Southern California regions. Our results show that a remote calibration can improve the accuracy of PM data, which was particularly visible for PM10. We highlight that sensor drift was mostly due to differences in particle composition rather than monitor operational factors. Thus, PM sensors may require frequent calibration if PM sources vary with different wind conditions or seasons.
Jia Liu, Guang-ya Wang, Can-can Zhu, Dong-hui Zhou, and Lin Wang
Atmos. Meas. Tech. Discuss.,
Revised manuscript accepted for AMTShort summary
Single-particle soot photometer (SP2) employs the core-shell model to represent coated BC particles, which introduces measurement errors of the mixing state (Dp / Dc) of BC. We construct fractal models to represent thinly and heavily coated BC particles, and the measurement errors of the mixing state are investigated from the numerical aspect. We find that errors in Dp / Dc are noteworthy, and the measurement errors can further affect the evaluation accuracy of the radiative forcing of BC.
Daniel A. Jaffe, Colleen Miller, Katie Thompson, Brandon Finley, Manna Nelson, James Ouimette, and Elisabeth Andrews
Atmos. Meas. Tech., 16, 1311–1322,Short summary
PurpleAir sensors (PASs) are low-cost tools to measure fine particulate matter (PM) concentrations. However, the raw PAS data have significant biases, so the sensors must be corrected. We analyzed data from numerous sites and found that the standard correction to the PAS Purple Air data is accurate in urban pollution events and smoke events but leads to a 6-fold underestimate in the PM2.5 concentrations in dust events. We propose a new correction algorithm to address this problem.
Yandong Tong, Lu Qi, Giulia Stefenelli, Dongyu Simon Wang, Francesco Canonaco, Urs Baltensperger, André Stephan Henry Prévôt, and Jay Gates Slowik
Atmos. Meas. Tech., 15, 7265–7291,Short summary
We present a method for positive matrix factorisation (PMF) analysis on a single dataset that includes measurements from both EESI-TOF and AMS in Zurich, Switzerland. For the first time, we resolved and quantified secondary organic aerosol (SOA) sources. Meanwhile, we also determined the retrieved EESI-TOF factor-dependent sensitivities. This method provides a framework for exploiting semi-quantitative, high-resolution instrumentation for quantitative source apportionment.
Zefeng Zhang, Hengnan Guo, Hanqing Kang, Jing Wang, Junlin An, Xingna Yu, Jingjing Lv, and Bin Zhu
Atmos. Meas. Tech., 15, 7259–7264,Short summary
In this study, we first analyze the relationship between the visibility, the extinction coefficient, and atmospheric compositions. Then we propose to use the harmonic average of visibility data as the average visibility, which can better reflect changes in atmospheric extinction coefficients and aerosol concentrations. It is recommended to use the harmonic average visibility in the studies of climate change, atmospheric radiation, air pollution, environmental health, etc.
Hyungwon John Park, Jeffrey S. Reid, Livia S. Freire, Christopher Jackson, and David H. Richter
Atmos. Meas. Tech., 15, 7171–7194,Short summary
We use numerical models to study field measurements of sea spray aerosol particles and conclude that both the atmospheric state and the methods of instrument sampling are causes for the variation in the production rate of aerosol particles: a critical metric to learn the aerosol's effect on processes like cloud physics and radiation. This work helps field observers improve their experimental design and interpretation of measurements because of turbulence in the atmosphere.
Christina Vasilakopoulou, Iasonas Stavroulas, Nikolaos Mihalopoulos, and Spyros N. Pandis
Atmos. Meas. Tech., 15, 6419–6431,Short summary
Offline aerosol mass spectrometer (AMS) measurements can provide valuable information about ambient organic aerosols when online AMS measurements are not available. In this study, we examine whether and how the low time resolution (usually 24 h) of the offline technique affects source apportionment results. We concluded that use of the daily averages resulted in estimated average contributions that were within 8 % of the total OA compared with the high-resolution analysis.
Priyanka deSouza, Ralph Kahn, Tehya Stockman, William Obermann, Ben Crawford, An Wang, James Crooks, Jing Li, and Patrick Kinney
Atmos. Meas. Tech., 15, 6309–6328,Short summary
How sensitive are the spatial and temporal trends of PM2.5 derived from a network of low-cost sensors to the calibration adjustment used? How transferable are calibration equations developed at a few co-location sites to an entire network of low-cost sensors? This paper attempts to answer this question and offers a series of suggestions on how to develop the most robust calibration function for different end uses. It uses measurements from the Love My Air network in Denver as a test case.
Sahil Bhandari, Zainab Arub, Gazala Habib, Joshua S. Apte, and Lea Hildebrandt Ruiz
Atmos. Meas. Tech., 15, 6051–6074,Short summary
We present a new method to conduct source apportionment resolved by time of day using the underlying approach of positive matrix factorization. We report results for four example time periods in two seasons (winter and monsoon 2017) in Delhi, India. Compared to the traditional approach, we extract a larger number of factors that represent the expected sources of primary organic aerosol. This method can capture diurnal time series patterns of sources at low computational cost.
Alireza Moallemi, Rob L. Modini, Tatyana Lapyonok, Anton Lopatin, David Fuertes, Oleg Dubovik, Philippe Giaccari, and Martin Gysel-Beer
Atmos. Meas. Tech., 15, 5619–5642,Short summary
Aerosol properties (size distributions, refractive indices) can be retrieved from in situ, angularly resolved light scattering measurements performed with polar nephelometers. We apply an established framework to assess the aerosol property retrieval potential for different instrument configurations, target applications, and assumed prior knowledge. We also demonstrate how a reductive greedy algorithm can be used to determine the optimal placements of the angular sensors in a polar nephelometer.
Marta Via, Gang Chen, Francesco Canonaco, Kaspar R. Daellenbach, Benjamin Chazeau, Hasna Chebaicheb, Jianhui Jiang, Hannes Keernik, Chunshui Lin, Nicolas Marchand, Cristina Marin, Colin O'Dowd, Jurgita Ovadnevaite, Jean-Eudes Petit, Michael Pikridas, Véronique Riffault, Jean Sciare, Jay G. Slowik, Leïla Simon, Jeni Vasilescu, Yunjiang Zhang, Olivier Favez, André S. H. Prévôt, Andrés Alastuey, and María Cruz Minguillón
Atmos. Meas. Tech., 15, 5479–5495,Short summary
This work presents the differences resulting from two techniques (rolling and seasonal) of the positive matrix factorisation model that can be run for organic aerosol source apportionment. The current state of the art suggests that the rolling technique is more accurate, but no proof of its effectiveness has been provided yet. This paper tackles this issue in the context of a synthetic dataset and a multi-site real-world comparison.
Sungwoo Kim, Brian M. Lerner, Donna T. Sueper, and Gabriel Isaacman-VanWertz
Atmos. Meas. Tech., 15, 5061–5075,Short summary
Atmospheric samples can be complex, and current analysis methods often require substantial human interaction and discard potentially important information. To improve analysis accuracy and computational cost of these large datasets, we developed an automated analysis algorithm that utilizes a factor analysis approach coupled with a decision tree. We demonstrate that this algorithm cataloged approximately 10 times more analytes compared to a manual analysis and in a quarter of the analysis time.
Olga Zografou, Maria Gini, Manousos I. Manousakas, Gang Chen, Athina C. Kalogridis, Evangelia Diapouli, Athina Pappa, and Konstantinos Eleftheriadis
Atmos. Meas. Tech., 15, 4675–4692,Short summary
A yearlong ToF-ACSM dataset was used to characterize ambient aerosols over a suburban Athenian site, and innovative software for source apportionment was implemented in order to distinguish the sources of the total non-refractory species of PM1. A comparison between the methodology of combined organic and inorganic PMF analysis and the conventional organic PMF took place.
Jeramy L. Dedrick, Georges Saliba, Abigail S. Williams, Lynn M. Russell, and Dan Lubin
Atmos. Meas. Tech., 15, 4171–4194,Short summary
A new method is presented to retrieve the sea spray aerosol size distribution by combining submicron size and nephelometer scattering based on Mie theory. Using available sea spray tracers, we find that this approach serves as a comparable substitute to supermicron size distribution measurements, which are limited in availability at marine sites. Application of this technique can expand sea spray observations and improve the characterization of marine aerosol impacts on clouds and climate.
Ivo Beck, Hélène Angot, Andrea Baccarini, Lubna Dada, Lauriane Quéléver, Tuija Jokinen, Tiia Laurila, Markus Lampimäki, Nicolas Bukowiecki, Matthew Boyer, Xianda Gong, Martin Gysel-Beer, Tuukka Petäjä, Jian Wang, and Julia Schmale
Atmos. Meas. Tech., 15, 4195–4224,Short summary
We present the pollution detection algorithm (PDA), a new method to identify local primary pollution in remote atmospheric aerosol and trace gas time series. The PDA identifies periods of contaminated data and relies only on the target dataset itself; i.e., it is independent of ancillary data such as meteorological variables. The parameters of all pollution identification steps are adjustable so that the PDA can be tuned to different locations and situations. It is available as open-access code.
Emily B. Franklin, Lindsay D. Yee, Bernard Aumont, Robert J. Weber, Paul Grigas, and Allen H. Goldstein
Atmos. Meas. Tech., 15, 3779–3803,Short summary
The composition of atmospheric aerosols are extremely complex, containing hundreds of thousands of estimated individual compounds. The majority of these compounds have never been catalogued in widely used databases, making them extremely difficult for atmospheric chemists to identify and analyze. In this work, we present Ch3MS-RF, a machine-learning-based model to enable characterization of complex mixtures and prediction of structure-specific properties of unidentifiable organic compounds.
Jiaoshi Zhang, Yang Wang, Steven Spielman, Susanne Hering, and Jian Wang
Atmos. Meas. Tech., 15, 2579–2590,Short summary
New nonparametric, regularized methods are developed to invert the growth factor probability density function (GF-PDF) from humidity-controlled fast integrated mobility spectrometer measurements. These algorithms are computationally efficient, require no prior assumptions of the GF-PDF distribution, and reduce the error in inverted GF-PDF. They can be applied to humidified tandem differential mobility analyzer data. Among all algorithms, Twomey’s method retrieves GF-PDF with the smallest error.
Douglas A. Day, Pedro Campuzano-Jost, Benjamin A. Nault, Brett B. Palm, Weiwei Hu, Hongyu Guo, Paul J. Wooldridge, Ronald C. Cohen, Kenneth S. Docherty, J. Alex Huffman, Suzane S. de Sá, Scot T. Martin, and Jose L. Jimenez
Atmos. Meas. Tech., 15, 459–483,Short summary
Particle-phase nitrates are an important component of atmospheric aerosols and chemistry. In this paper, we systematically explore the application of aerosol mass spectrometry (AMS) to quantify the organic and inorganic nitrate fractions of aerosols in the atmosphere. While AMS has been used for a decade to quantify nitrates, methods are not standardized. We make recommendations for a more universal approach based on this analysis of a large range of field and laboratory observations.
Markus D. Petters
Atmos. Meas. Tech., 14, 7909–7928,Short summary
Inverse methods infer physical properties from a measured instrument response. Measurement noise often interferes with the inversion. This work presents a general, domain-independent, accessible, and computationally efficient software implementation of a common class of statistical inversion methods. In addition, a new method to invert data from humidified tandem differential mobility analyzers is introduced. Results show that the approach is suitable for inversion of large-scale datasets.
Pak Lun Fung, Martha Arbayani Zaidan, Ola Surakhi, Sasu Tarkoma, Tuukka Petäjä, and Tareq Hussein
Atmos. Meas. Tech., 14, 5535–5554,Short summary
Aerosol size distribution measurements rely on a variety of techniques to classify the aerosol size and measure the size distribution. However, due to the instrumental insufficiency and inversion limitations, the raw dataset contains missing gaps or negative values, which hinder further analysis. With a merged particle size distribution in Jordan, this paper suggests a neural network method to estimate number concentrations at a particular size bin by the number concentration at other size bins.
Xiansheng Liu, Hadiatullah Hadiatullah, Xun Zhang, L. Drew Hill, Andrew H. A. White, Jürgen Schnelle-Kreis, Jan Bendl, Gert Jakobi, Brigitte Schloter-Hai, and Ralf Zimmermann
Atmos. Meas. Tech., 14, 5139–5151,Short summary
A monitoring campaign was conducted in Augsburg to determine a suitable noise reduction algorithm for the MA200 Aethalometer. Results showed that centred moving average (CMA) post-processing effectively removed spurious negative concentrations without major bias and reliably highlighted effects from local sources, effectively increasing spatio-temporal resolution in mobile measurements. Evaluation of each method on peak sample reduction and background correction further supports the reliability.
Jie Qiu, Wangshu Tan, Gang Zhao, Yingli Yu, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 4879–4891,Short summary
Considering nephelometers' major problems of a nonideal Lambertian light source and angle truncation, a new correction method based on a machine learning model is proposed. Our method has the advantage of obtaining data with high accuracy while achieving self-correction, which means that researchers can get more accurate scattering coefficients without the need for additional observation data. This method provides a more precise estimation of the aerosol’s direct radiative forcing.
Amir Yazdani, Ann M. Dillner, and Satoshi Takahama
Atmos. Meas. Tech., 14, 4805–4827,Short summary
We propose a spectroscopic method for estimating several mixture-averaged molecular properties (carbon number and molecular weight) in particulate matter relevant for understanding its chemical origins. This estimation is enabled by calibration models built and tested using laboratory standards containing molecules with known structure, and can be applied to filter samples of PM2.5 currently collected in existing air pollution monitoring networks and field campaigns.
Atmos. Meas. Tech., 14, 3707–3719,Short summary
The Aethalometer model is used widely for estimating the contributions of fossil fuel emissions and biomass burning to black carbon. The calculation is based on measured absorption Ångström exponents, which is ambiguous since it not only depends on the dominant absorber but also on the size and internal structure of the particles, core size, and shell thickness. The uncertainties of the fractions of absorption by eBC from fossil fuel and biomass burning are evaluated with a core–shell Mie model.
Weiqi Xu, Masayuki Takeuchi, Chun Chen, Yanmei Qiu, Conghui Xie, Wanyun Xu, Nan Ma, Douglas R. Worsnop, Nga Lee Ng, and Yele Sun
Atmos. Meas. Tech., 14, 3693–3705,Short summary
Here we developed a method for estimation of particulate organic nitrates (pON) from the measurements of a high-resolution aerosol mass spectrometer coupled with a thermodenuder based on the volatility differences between inorganic nitrate and pON. The results generally had improvements in reducing negative values due to the influences of a high concentration of inorganic nitrate and a constant ratio of NO+ to NO2+ of organic nitrates (RON).
Melinda K. Schueneman, Benjamin A. Nault, Pedro Campuzano-Jost, Duseong S. Jo, Douglas A. Day, Jason C. Schroder, Brett B. Palm, Alma Hodzic, Jack E. Dibb, and Jose L. Jimenez
Atmos. Meas. Tech., 14, 2237–2260,Short summary
This work focuses on two important properties of the aerosol, acidity, and sulfate composition, which is important for our understanding of aerosol health and environmental impacts. We explore different methods to understand the composition of the aerosol with measurements from a specific instrument and apply those methods to a large dataset. These measurements are confounded by other factors, making it challenging to predict aerosol sulfate composition; pH estimations, however, show promise.
Weilun Zhao, Wangshu Tan, Gang Zhao, Chuanyang Shen, Yingli Yu, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 1319–1331,
Chuanyang Shen, Gang Zhao, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 1293–1301,Short summary
Aerosol hygroscopicity measured by the humidified tandem differential mobility analyzer (HTDMA) is affected by multiply charged particles from two aspects: (1) number contribution and (2) the weakening effect. An algorithm is proposed to do the multi-charge correction and applied to a field measurement. Results show that the difference between corrected and measured size-resolved κ can reach 0.05, highlighting that special attention needs to be paid to the multi-charge effect when using HTDMA.
Francesco Canonaco, Anna Tobler, Gang Chen, Yulia Sosedova, Jay Gates Slowik, Carlo Bozzetti, Kaspar Rudolf Daellenbach, Imad El Haddad, Monica Crippa, Ru-Jin Huang, Markus Furger, Urs Baltensperger, and André Stephan Henry Prévôt
Atmos. Meas. Tech., 14, 923–943,Short summary
Long-term ambient aerosol mass spectrometric data were analyzed with a statistical model (PMF) to obtain source contributions and fingerprints. The new aspects of this paper involve time-dependent source fingerprints by a rolling technique and the replacement of the full visual inspection of each run by a user-defined set of criteria to monitor the quality of each of these runs more efficiently. More reliable sources will finally provide better instruments for political mitigation strategies.
Kenji Miki and Shigeto Kawashima
Atmos. Meas. Tech., 14, 685–693,Short summary
Laser optics have long been used in pollen counting systems. To clarify the limitations and potential new applications of laser optics for automatic pollen counting and discrimination, we determined the light scattering patterns of various pollen types, tracked temporal changes in these distributions, and introduced a new theory for automatic pollen discrimination.
Yinchao Zhang, Su Chen, Siying Chen, He Chen, and Pan Guo
Atmos. Meas. Tech., 13, 6675–6689,Short summary
Air pollution has an important impact on human health, climatic patterns, and the ecological environment. The complexity of the nocturnal boundary layer (NBL), combined with its strong physio-chemical effect, induces worse polluted episodes. Therefore, we present a new approach named cluster analysis of gradient method (CA-GM) to overcome the multilayer structure and remove the fluctuation of NBL height using raw data resolution.
Tommy Chan, Runlong Cai, Lauri R. Ahonen, Yiliang Liu, Ying Zhou, Joonas Vanhanen, Lubna Dada, Yan Chao, Yongchun Liu, Lin Wang, Markku Kulmala, and Juha Kangasluoma
Atmos. Meas. Tech., 13, 4885–4898,Short summary
Using a particle size magnifier (PSM; Airmodus, Finland), we determined the particle size distribution using four inversion methods and compared each method to the others to establish their strengths and weaknesses. Furthermore, we provided a step-by-step procedure on how to invert measured data using the PSM. Finally, we provided recommendations, code and data related to the data inversion. This is an important paper, as no operating procedure exists regarding how to process measured PSM data.
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Yong Lin, Alfred Wiedensohler, Michael Schulz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäja, Sang-Woo Kim, Wenche Aas, Jean-Philippe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, A. Gannet Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Sebastiao Martins Dos Santos, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Pérez, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Toczko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
Atmos. Meas. Tech., 13, 4353–4392,Short summary
The paper establishes the fiducial reference of the GAW aerosol network providing the fully characterized value chain to the provision of four climate-relevant aerosol properties from ground-based sites. Data from almost 90 stations worldwide are reported for a reference year, 2017, providing a unique and very robust view of the variability of these variables worldwide. Current gaps in the GAW network are analysed and requirements for the Global Climate Monitoring System are proposed.
Shengqiang Zhu, Lei Li, Shurong Wang, Mei Li, Yaxi Liu, Xiaohui Lu, Hong Chen, Lin Wang, Jianmin Chen, Zhen Zhou, Xin Yang, and Xiaofei Wang
Atmos. Meas. Tech., 13, 4111–4121,Short summary
Single-particle aerosol mass spectrometry (SPAMS) is widely used to detect chemical compositions and sizes of individual aerosol particles. However, it has a major issue: the mass accuracy of high-resolution SPAMS is relatively low. Here we developed an automatic linear calibration method to greatly improve the mass accuracy of SPAMS spectra so that the elemental compositions of organic peaks, such as Cx, CxHy, CxHyOz and CxHyNO peaks, can be directly identified just based on their m / z values.
William Wandji Nyamsi, Antti Lipponen, Arturo Sanchez-Lorenzo, Martin Wild, and Antti Arola
Atmos. Meas. Tech., 13, 3061–3079,Short summary
This paper proposes a novel and accurate method for estimating and reconstructing aerosol optical depth from sunshine duration measurements under cloud-free conditions at any place and time since the late 19th century. The method performs very well when compared to AErosol RObotic NETwork measurements and operates an efficient detection of signals from massive volcanic eruptions. Reconstructed long-term aerosol optical depths are in agreement with the dimming/brightening phenomenon.
Sascha Pfeifer, Thomas Müller, Andrew Freedman, and Alfred Wiedensohler
Atmos. Meas. Tech., 13, 2161–2167,Short summary
The effect of the baseline drift on the resulting extinction values of three CAPS PMex monitors with different wavelengths was analysed for an urban background station. A significant baseline drift was observed, which leads to characteristic measurement artefacts for particle extinction. Two alternative methods for recalculating the baseline are shown. With these methods the extinction artefacts are diminished and the effective scattering of the resulting extinction values is reduced.
Stuart K. Grange, Hanspeter Lötscher, Andrea Fischer, Lukas Emmenegger, and Christoph Hueglin
Atmos. Meas. Tech., 13, 1867–1885,Short summary
Black carbon (BC) is an important atmospheric pollutant and can be monitored by instruments called aethalometers. A pragmatic data processing technique called the
aethalometer modelcan be used to apportion aethalometer observations into traffic and woodburning components. We present an exploratory data analysis evaluating the aethalometer model and use the outputs for BC trend analysis across Switzerland. The aethalometer model's robustness and utility for such analyses is discussed.
Charlotte Bürki, Matteo Reggente, Ann M. Dillner, Jenny L. Hand, Stephanie L. Shaw, and Satoshi Takahama
Atmos. Meas. Tech., 13, 1517–1538,Short summary
Infrared spectroscopy is a chemically informative method for particulate matter characterization. However, recent work has demonstrated that predictions depend heavily on the choice of calibration model parameters. We propose a means for managing parameter uncertainties by combining available data from laboratory standards, molecular databases, and collocated ambient measurements to provide useful characterization of atmospheric organic matter on a large scale.
Kaixu Bai, Ke Li, Jianping Guo, Yuanjian Yang, and Ni-Bin Chang
Atmos. Meas. Tech., 13, 1213–1226,Short summary
A novel gap-filling method called the diurnal-cycle-constrained empirical orthogonal function (DCCEOF) is proposed. Cross validation indicates that this method gives high accuracy in predicting missing values in daily PM2.5 time series by accounting for the local diurnal phases, especially by reconstructing daily extrema that cannot be accurately restored by other approaches. The DCCEOF method can be easily applied to other data sets because of its self-consistent capability.
Tongshu Zheng, Michael H. Bergin, Ronak Sutaria, Sachchida N. Tripathi, Robert Caldow, and David E. Carlson
Atmos. Meas. Tech., 12, 5161–5181,Short summary
Here we present a simultaneous Gaussian process regression (GPR) and linear regression pipeline to calibrate and monitor dense wireless low-cost particulate matter sensor networks (WLPMSNs) on the fly by using all available reference monitors across an area. Our approach can achieve an overall 30 % prediction error at a 24 h scale, can differentiate malfunctioning nodes, and track drift. Our solution can substantially reduce manual labor for managing WLPMSNs and prolong their lifetimes.
Stina Ausmeel, Axel Eriksson, Erik Ahlberg, and Adam Kristensson
Atmos. Meas. Tech., 12, 4479–4493,Short summary
We present a method for identifying individual exhaust plumes of air pollution emitted from shipping, by linking these to specific ships using identification information which all ships transmit. We also quantify the contribution of these plumes to local particle levels, which has relevance for health effects. Ships emit a lot of nanometre-sized particles, which proved to be a good indicator of plumes at a distance of about 10 km downwind of a shipping lane in the Baltic Sea.
Ingrida Šaulienė, Laura Šukienė, Gintautas Daunys, Gediminas Valiulis, Lukas Vaitkevičius, Predrag Matavulj, Sanja Brdar, Marko Panic, Branko Sikoparija, Bernard Clot, Benoît Crouzy, and Mikhail Sofiev
Atmos. Meas. Tech., 12, 3435–3452,Short summary
The goal is to evaluate the capabilities of the new Rapid-E monitor and to construct a first-level pollen recognition algorithm. The output data were treated with ANN aiming at classification of the injected pollen. Algorithms based on scattering and fluorescence data alone fall short of acceptable quality. The combinations of these exceeded 80 % accuracy for 5 out of 11 pollen species. Constructing multistep algorithms with sequential discrimination of pollen can be a possible way forward.
Matteo Reggente, Rudolf Höhn, and Satoshi Takahama
Atmos. Meas. Tech., 12, 2313–2329,Short summary
The infrared spectra of atmospheric particles are rich in chemical information but require sophisticated statistical methods to extract information on account of their complex absorption profiles. We present an open software suite which makes current algorithms used for analysis of such spectra available to the community, with a browser-based interface for general users and modular architecture that facilitates addition of new methods by developers.
Xiaoli Shen, Harald Saathoff, Wei Huang, Claudia Mohr, Ramakrishna Ramisetty, and Thomas Leisner
Atmos. Meas. Tech., 12, 2219–2240,Short summary
Based on single-particle mass spectra from field measurements in the upper Rhine valley, we identified characteristic particle classes and estimated their mass contributions without the need of a reference instrument in the field. Our study provides a good example for quantitative interpretation of single-particle data. Together with the complimentary results from bulk measurements, we have shown how a better understanding of the mixing state of ambient aerosol particles can be achieved.
Tarjei Antonsen, Ove Havnes, and Andres Spicher
Atmos. Meas. Tech., 12, 2139–2153,Short summary
This paper presents measurements of changes in mesospheric aerosol populations on different length scales, as detected by the DUSTY and MUDD probes on the MAXIDUSTY-1B rocket on 8 July 2016. Identical probes recorded very different currents, which we attribute to adverse flow effects. We find a general anti-correlation for charged aerosols and electrons, but not consistently on all length scales. We conclude that there is no simple relationship between aerosols and PMSE (radar echoes).
Ove Havnes, Tarjei Antonsen, Gerd Baumgarten, Thomas W. Hartquist, Alexander Biebricher, Åshild Fredriksen, Martin Friedrich, and Jonas Hedin
Atmos. Meas. Tech., 12, 1673–1683,Short summary
We present a new method of analyzing data from rocket-borne aerosol detectors of the Faraday cup type (DUSTY). By using models for how aerosols are charged in the mesosphere and how they interact in a collision with the probes, fundamental parameters like aerosol radius, charge, and number density can be derived. The resolution can be down to ~ 10 cm, which is much lower than other available methods. The theory is furthermore used to analyze DUSTY data from the 2016 rocket campaign MAXIDUSTY.
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Bai, K., Li, K., Chang, N.-B., and Gao, W.: Advancing the prediction accuracy of satellite-based PM2.5 concentration mapping: A perspective of data mining through in situ PM2.5 measurements, Environ. Pollut., 254, 113047, https://doi.org/10.1016/j.envpol.2019.113047, 2019.
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Che, H., Xia, X., Zhu, J., Li, Z., Dubovik, O., Holben, B., Goloub, P., Chen, H., Estelles, V., Cuevas-Agulló, E., Blarel, L., Wang, H., Zhao, H., Zhang, X., Wang, Y., Sun, J., Tao, R., Zhang, X., and Shi, G.: Column aerosol optical properties and aerosol radiative forcing during a serious haze-fog month over North China Plain in 2013 based on ground-based sunphotometer measurements, Atmos. Chem. Phys., 14, 2125–2138, https://doi.org/10.5194/acp-14-2125-2014, 2014.
Che, H. Z., Shi, G. Y., Zhang, X. Y., Arimoto, R., Zhao, J. Q., Xu, L., Wang, B., and Chen, Z. H.: Analysis of 40 years of solar radiation data from China, 1961–2000, Geophys. Res. Lett., 32, L06803, https://doi.org/10.1029/2004GL022322, 2005.
Chen, S., Yang, Y., Deng, F., Zhang, Y., Liu, D., Liu, C., and Gao, Z.: A high-resolution monitoring approach of canopy urban heat island using a random forest model and multi-platform observations, Atmos. Meas. Tech., 15, 735–756, https://doi.org/10.5194/amt-15-735-2022, 2022.
Chen, W., Wang, X., Cohen, J. B., Zhou, S., Zhang, Z., Chang, M., and Chan, C.-Y.: Properties of aerosols and formation mechanisms over southern China during the monsoon season, Atmos. Chem. Phys., 16, 13271–13289, https://doi.org/10.5194/acp-16-13271-2016, 2016.
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The Guangdong–Hong Kong–Macao Greater Bay Area suffers from summertime air pollution events related to typhoons. The present study leverages machine learning to predict typhoon-associated air quality over the area. The model evaluation shows that the model performs excellently. Moreover, the change in meteorological drivers of air quality on typhoon days and non-typhoon days suggests that air pollution control strategies should have different focuses on typhoon days and non-typhoon days.
The Guangdong–Hong Kong–Macao Greater Bay Area suffers from summertime air pollution events...