Articles | Volume 21, issue 9
https://doi.org/10.5194/acp-21-7199-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-7199-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 May 2021
Research article |
| 11 May 2021
| 11 May 2021
Mobile monitoring of urban air quality at high spatial resolution by low-cost sensors: impacts of COVID-19 pandemic lockdown
Shibao Wang
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Yun Ma
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Zhongrui Wang
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Lei Wang
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Xuguang Chi
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Aijun Ding
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Mingzhi Yao
Beijing SPC Environment Protection Tech Company Ltd., Beijing, China
Yunpeng Li
Beijing SPC Environment Protection Tech Company Ltd., Beijing, China
Qilin Li
Beijing SPC Environment Protection Tech Company Ltd., Beijing, China
Mengxian Wu
Hebei Sailhero Environmental Protection Hi-tech. Ltd.,
Shijiazhuang, Hebei, China
Ling Zhang
Hebei Sailhero Environmental Protection Hi-tech. Ltd.,
Shijiazhuang, Hebei, China
Yongle Xiao
Hebei Sailhero Environmental Protection Hi-tech. Ltd.,
Shijiazhuang, Hebei, China
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Related authors
Yanxu Zhang, Xingpei Ye, Shibao Wang, Xiaojing He, Lingyao Dong, Ning Zhang, Haikun Wang, Zhongrui Wang, Yun Ma, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Ling Zhang, and Yongle Xiao
Atmos. Chem. Phys., 21, 2917–2929, https://doi.org/10.5194/acp-21-2917-2021, https://doi.org/10.5194/acp-21-2917-2021, 2021
Short summary
Short summary
Urban air quality varies drastically at street scale, but traditional methods are too coarse to resolve it. We develop a 10 m resolution air quality model and apply it for traffic-related carbon monoxide air quality in Nanjing megacity. The model reveals a detailed geographical dispersion pattern of air pollution in and out of the road network and agrees well with a validation dataset. The model can be a vigorous part of the smart city system and inform urban planning and air quality management.
Mao Mao, Yujuan Wang, Peipei Wu, Shaojian Huang, Zhengcheng Song, and Yanxu Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-3307, https://doi.org/10.5194/egusphere-2025-3307, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
This study examines how radionuclides released from nuclear power plants are transported and transformed in the global ocean over time. Using an advanced ocean simulation model, it focuses on radionuclides released during the Fukushima accident and from planned wastewater discharges. The findings show that some radionuclides can travel across the Pacific within a few years and gradually spread to other ocean basins by mid-century, emphasizing potential long-term environmental impacts.
Sijia Lou, Manish Shrivastava, Alexandre Albinet, Sophie Tomaz, Deepchandra Srivastava, Olivier Favez, Huizhong Shen, and Aijun Ding
Atmos. Chem. Phys., 25, 8163–8183, https://doi.org/10.5194/acp-25-8163-2025, https://doi.org/10.5194/acp-25-8163-2025, 2025
Short summary
Short summary
Polycyclic aromatic hydrocarbons (PAHs), emitted from incomplete combustion, pose serious health risks due to their carcinogenic properties. This research demonstrates that viscous organic aerosol coatings significantly hinder PAH oxidation, with spatial distributions sensitive to the degradation modeling approach. Our findings emphasize the need for accurate modeling of PAH oxidation processes in risk assessments, considering both fresh and oxidized PAHs in evaluating human health risks.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
Short summary
Short summary
This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Junchao Yin, Yuliang Liu, Wei Nie, Chao Yan, Qiaozhi Zha, Yuanyuan Li, Dafeng Ge, Chong Liu, Caijun Zhu, Xuguang Chi, and Aijun Ding
EGUsphere, https://doi.org/10.5194/egusphere-2025-1371, https://doi.org/10.5194/egusphere-2025-1371, 2025
Short summary
Short summary
Atmospheric aerosols affect human health and climate change, yet understanding their formation remains challenging. We studied oxygenated organic molecules, key intermediates, in a complex urban environment in China. Using an advanced analytical method, we identified major chemical pathways and how environmental factors influence them. Our findings enhance the understanding of atmospheric chemistry, offering insights for better environmental and climate policies.
Zeyuan Tian, Jiandong Wang, Jiaping Wang, Chao Liu, Jia Xing, Jinbo Wang, Zhouyang Zhang, Yuzhi Jin, Sunan Shen, Bin Wang, Wei Nie, Xin Huang, and Aijun Ding
Atmos. Meas. Tech., 18, 1149–1162, https://doi.org/10.5194/amt-18-1149-2025, https://doi.org/10.5194/amt-18-1149-2025, 2025
Short summary
Short summary
The radiative effect of black carbon (BC) is substantially modulated by its mixing state, which is challenging to derive physically with a single-particle soot photometer. This study establishes a machine-learning-based inversion model which can accurately and efficiently acquire the BC mixing state. Compared to the widely used leading-edge-only method, our model utilizes a broader scattering signal coverage to more accurately capture diverse particle characteristics.
Yuzhi Jin, Jiandong Wang, Chao Liu, David C. Wong, Golam Sarwar, Kathleen M. Fahey, Shang Wu, Jiaping Wang, Jing Cai, Zeyuan Tian, Zhouyang Zhang, Jia Xing, Aijun Ding, and Shuxiao Wang
Atmos. Chem. Phys., 25, 2613–2630, https://doi.org/10.5194/acp-25-2613-2025, https://doi.org/10.5194/acp-25-2613-2025, 2025
Short summary
Short summary
Black carbon (BC) affects climate and the environment, and its aging process alters its properties. Current models, like WRF-CMAQ, lack full accounting for it. We developed the WRF-CMAQ-BCG model to better represent BC aging by introducing bare and coated BC species and their conversion. The WRF-CMAQ-BCG model introduces the capability to simulate BC mixing states and bare and coated BC wet deposition, and it improves the accuracy of BC mass concentration and aerosol optics.
Tinghan Zhang, Ximeng Qi, Janne Lampilahti, Liangduo Chen, Xuguang Chi, Wei Nie, Xin Huang, Zehao Zou, Wei Du, Tom Kokkonen, Tuukka Petäjä, Katrianne Lehtipalo, Veli-Matti Kerminen, Aijun Ding, and Markku Kulmala
EGUsphere, https://doi.org/10.5194/egusphere-2024-3370, https://doi.org/10.5194/egusphere-2024-3370, 2025
Short summary
Short summary
By comparing air ions at two “flagship” sites —the SMEAR II site in the boreal forest of Finland and the SORPES site in a megacity in eastern China—we characterized ion concentrations and their roles in new particle formation (NPF) across contrasting environments. The ion-induced fraction was much higher in clean areas. However, earlier activation of charged particles and high ion-induced fraction during quiet NPF at SORPES imply a non-negligible role for ion-induced NPF in polluted areas.
Zhouyang Zhang, Jiandong Wang, Jiaping Wang, Nicole Riemer, Chao Liu, Yuzhi Jin, Zeyuan Tian, Jing Cai, Yueyue Cheng, Ganzhen Chen, Bin Wang, Shuxiao Wang, and Aijun Ding
Atmos. Chem. Phys., 25, 1869–1881, https://doi.org/10.5194/acp-25-1869-2025, https://doi.org/10.5194/acp-25-1869-2025, 2025
Short summary
Short summary
Black carbon (BC) exerts notable warming effects. We use a particle-resolved model to investigate the long-term behavior of the BC mixing state, revealing its compositions, coating thickness distribution, and optical properties all stabilize with a characteristic time of less than 1 d. This study can effectively simplify the description of the BC mixing state, which facilitates the precise assessment of the optical properties of BC aerosols in global and chemical transport models.
Ling Li, Peipei Wu, Peng Zhang, Shaojian Huang, and Yanxu Zhang
Geosci. Model Dev., 17, 8683–8695, https://doi.org/10.5194/gmd-17-8683-2024, https://doi.org/10.5194/gmd-17-8683-2024, 2024
Short summary
Short summary
In this study, we incorporate sea surfactants and wave-breaking processes into MITgcm-ECCOv4-Hg. The updated model shows increased fluxes in high-wind-speed and high-wave regions and vice versa, enhancing spatial heterogeneity. It shows that elemental mercury (Hg0) transfer velocity is more sensitive to wind speed. These findings may elucidate the discrepancies in previous estimations and offer insights into global Hg cycling.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Short summary
This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Jinbo Wang, Jiaping Wang, Yuxuan Zhang, Tengyu Liu, Xuguang Chi, Xin Huang, Dafeng Ge, Shiyi Lai, Caijun Zhu, Lei Wang, Qiaozhi Zha, Ximeng Qi, Wei Nie, Congbin Fu, and Aijun Ding
Atmos. Chem. Phys., 24, 11063–11080, https://doi.org/10.5194/acp-24-11063-2024, https://doi.org/10.5194/acp-24-11063-2024, 2024
Short summary
Short summary
In this study, we found large spatial discrepancies in the physical and chemical properties of black carbon over the Tibetan Plateau (TP). Elevated anthropogenic emissions from low-altitude regions can significantly change the mass concentration, mixing state and chemical composition of black-carbon-containing aerosol in the TP region, further altering its light absorption ability. Our study emphasizes the vulnerability of remote plateau regions to intense anthropogenic influences.
Wenxuan Hua, Sijia Lou, Xin Huang, Lian Xue, Ke Ding, Zilin Wang, and Aijun Ding
Atmos. Chem. Phys., 24, 6787–6807, https://doi.org/10.5194/acp-24-6787-2024, https://doi.org/10.5194/acp-24-6787-2024, 2024
Short summary
Short summary
In this study, we diagnose uncertainties in carbon monoxide and organic carbon emissions from four inventories for seven major wildfire-prone regions. Uncertainties in vegetation classification methods, fire detection products, and cloud obscuration effects lead to bias in these biomass burning (BB) emission inventories. By comparing simulations with measurements, we provide certain inventory recommendations. Our study has implications for reducing uncertainties in emissions in further studies.
Markku Kulmala, Diego Aliaga, Santeri Tuovinen, Runlong Cai, Heikki Junninen, Chao Yan, Federico Bianchi, Yafang Cheng, Aijun Ding, Douglas R. Worsnop, Tuukka Petäjä, Katrianne Lehtipalo, Pauli Paasonen, and Veli-Matti Kerminen
Aerosol Research, 2, 49–58, https://doi.org/10.5194/ar-2-49-2024, https://doi.org/10.5194/ar-2-49-2024, 2024
Short summary
Short summary
Atmospheric new particle formation (NPF), together with secondary production of particulate matter in the atmosphere, dominates aerosol particle number concentrations and submicron particle mass loads in many environments globally. In this opinion paper, we describe the paradigm shift to understand NPF in a continuous way instead of using traditional binary event–non-event analysis.
Yueyue Cheng, Chao Liu, Jiandong Wang, Jiaping Wang, Zhouyang Zhang, Li Chen, Dafeng Ge, Caijun Zhu, Jinbo Wang, and Aijun Ding
Atmos. Chem. Phys., 24, 3065–3078, https://doi.org/10.5194/acp-24-3065-2024, https://doi.org/10.5194/acp-24-3065-2024, 2024
Short summary
Short summary
Brown carbon (BrC), a light-absorbing aerosol, plays a pivotal role in influencing global climate. However, assessing BrC radiative effects remains challenging because the required observational data are hardly accessible. Here we develop a new BrC radiative effect estimation method combining conventional observations and numerical models. Our findings reveal that BrC absorbs up to a third of the sunlight at 370 nm that black carbon does, highlighting its importance in aerosol radiative effects.
Shiyi Lai, Ximeng Qi, Xin Huang, Sijia Lou, Xuguang Chi, Liangduo Chen, Chong Liu, Yuliang Liu, Chao Yan, Mengmeng Li, Tengyu Liu, Wei Nie, Veli-Matti Kerminen, Tuukka Petäjä, Markku Kulmala, and Aijun Ding
Atmos. Chem. Phys., 24, 2535–2553, https://doi.org/10.5194/acp-24-2535-2024, https://doi.org/10.5194/acp-24-2535-2024, 2024
Short summary
Short summary
By combining in situ measurements and chemical transport modeling, this study investigates new particle formation (NPF) on the southeastern Tibetan Plateau. We found that the NPF was driven by the presence of biogenic gases and the transport of anthropogenic precursors. The NPF was vertically heterogeneous and shaped by the vertical mixing. This study highlights the importance of anthropogenic–biogenic interactions and meteorological dynamics in NPF in this climate-sensitive region.
Shuzheng Guo, Chunxiang Ye, Weili Lin, Yi Chen, Limin Zeng, Xuena Yu, Jinhui Cui, Chong Zhang, Jing Duan, Haobin Zhong, Rujin Huang, Xuguang Chi, Wei Nie, and Aijun Ding
EGUsphere, https://doi.org/10.5194/egusphere-2024-262, https://doi.org/10.5194/egusphere-2024-262, 2024
Preprint archived
Short summary
Short summary
@Tibet field campaigns 2021 discovered surprisingly high levels and activity contributions of oxygenated volatile organic compounds on the southeast of the Tibetan Plateau, which suggests that OVOCs may play a larger role in the chemical reactions that occur in high-altitude regions than previously thought.
Ying Zhang, Duzitian Li, Xu-Cheng He, Wei Nie, Chenjuan Deng, Runlong Cai, Yuliang Liu, Yishuo Guo, Chong Liu, Yiran Li, Liangduo Chen, Yuanyuan Li, Chenjie Hua, Tingyu Liu, Zongcheng Wang, Jiali Xie, Lei Wang, Tuukka Petäjä, Federico Bianchi, Ximeng Qi, Xuguang Chi, Pauli Paasonen, Yongchun Liu, Chao Yan, Jingkun Jiang, Aijun Ding, and Markku Kulmala
Atmos. Chem. Phys., 24, 1873–1893, https://doi.org/10.5194/acp-24-1873-2024, https://doi.org/10.5194/acp-24-1873-2024, 2024
Short summary
Short summary
This study conducts a long-term observation of gaseous iodine oxoacids in two Chinese megacities, revealing their ubiquitous presence with peak concentrations (up to 0.1 pptv) in summer. Our analysis suggests a mix of terrestrial and marine sources for iodine. Additionally, iodic acid is identified as a notable contributor to sub-3 nm particle growth and particle survival probability.
Zhen Peng, Lili Lei, Zhe-Min Tan, Meigen Zhang, Aijun Ding, and Xingxia Kou
Atmos. Chem. Phys., 23, 14505–14520, https://doi.org/10.5194/acp-23-14505-2023, https://doi.org/10.5194/acp-23-14505-2023, 2023
Short summary
Short summary
Annual PM2.5 emissions in China consistently decreased by about 3% to 5% from 2017 to 2020 with spatial variations and seasonal dependencies. High-temporal-resolution and dynamics-based PM2.5 emission estimates provide quantitative diurnal variations for each season. Significant reductions in PM2.5 emissions in the North China Plain and northeast of China in 2020 were caused by COVID-19.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
Short summary
Short summary
In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Guangdong Niu, Ximeng Qi, Liangduo Chen, Lian Xue, Shiyi Lai, Xin Huang, Jiaping Wang, Xuguang Chi, Wei Nie, Veli-Matti Kerminen, Tuukka Petäjä, Markku Kulmala, and Aijun Ding
Atmos. Chem. Phys., 23, 7521–7534, https://doi.org/10.5194/acp-23-7521-2023, https://doi.org/10.5194/acp-23-7521-2023, 2023
Short summary
Short summary
The reported below-cloud wet-scavenging coefficients (BWSCs) are much higher than theoretical data, but the reason remains unclear. Based on long-term observation, we find that air mass changing during rainfall events causes the overestimation of BWSCs. Thus, the discrepancy in BWSCs between observation and theory is not as large as currently believed. To obtain reasonable BWSCs and parameterizations from field observations, the effect of air mass changes needs to be considered.
Chuanhua Ren, Xin Huang, Tengyu Liu, Yu Song, Zhang Wen, Xuejun Liu, Aijun Ding, and Tong Zhu
Geosci. Model Dev., 16, 1641–1659, https://doi.org/10.5194/gmd-16-1641-2023, https://doi.org/10.5194/gmd-16-1641-2023, 2023
Short summary
Short summary
Ammonia in the atmosphere has wide impacts on the ecological environment and air quality, and its emission from soil volatilization is highly sensitive to meteorology, making it challenging to be well captured in models. We developed a dynamic emission model capable of calculating ammonia emission interactively with meteorological and soil conditions. Such a coupling of soil emission with meteorology provides a better understanding of ammonia emission and its contribution to atmospheric aerosol.
Chao Yan, Yicheng Shen, Dominik Stolzenburg, Lubna Dada, Ximeng Qi, Simo Hakala, Anu-Maija Sundström, Yishuo Guo, Antti Lipponen, Tom V. Kokkonen, Jenni Kontkanen, Runlong Cai, Jing Cai, Tommy Chan, Liangduo Chen, Biwu Chu, Chenjuan Deng, Wei Du, Xiaolong Fan, Xu-Cheng He, Juha Kangasluoma, Joni Kujansuu, Mona Kurppa, Chang Li, Yiran Li, Zhuohui Lin, Yiliang Liu, Yuliang Liu, Yiqun Lu, Wei Nie, Jouni Pulliainen, Xiaohui Qiao, Yonghong Wang, Yifan Wen, Ye Wu, Gan Yang, Lei Yao, Rujing Yin, Gen Zhang, Shaojun Zhang, Feixue Zheng, Ying Zhou, Antti Arola, Johanna Tamminen, Pauli Paasonen, Yele Sun, Lin Wang, Neil M. Donahue, Yongchun Liu, Federico Bianchi, Kaspar R. Daellenbach, Douglas R. Worsnop, Veli-Matti Kerminen, Tuukka Petäjä, Aijun Ding, Jingkun Jiang, and Markku Kulmala
Atmos. Chem. Phys., 22, 12207–12220, https://doi.org/10.5194/acp-22-12207-2022, https://doi.org/10.5194/acp-22-12207-2022, 2022
Short summary
Short summary
Atmospheric new particle formation (NPF) is a dominant source of atmospheric ultrafine particles. In urban environments, traffic emissions are a major source of primary pollutants, but their contribution to NPF remains under debate. During the COVID-19 lockdown, traffic emissions were significantly reduced, providing a unique chance to examine their relevance to NPF. Based on our comprehensive measurements, we demonstrate that traffic emissions alone are not able to explain the NPF in Beijing.
Xiaotian Xu, Xu Feng, Haipeng Lin, Peng Zhang, Shaojian Huang, Zhengcheng Song, Yiming Peng, Tzung-May Fu, and Yanxu Zhang
Geosci. Model Dev., 15, 3845–3859, https://doi.org/10.5194/gmd-15-3845-2022, https://doi.org/10.5194/gmd-15-3845-2022, 2022
Short summary
Short summary
Mercury is one of the most toxic pollutants in the environment, and wet deposition is a major process for atmospheric mercury to enter, causing ecological and human health risks. High-mercury wet deposition in the southeastern US has been a problem for many years. Here we employed a newly developed high-resolution WRF-GC model with the capability to simulate mercury to study this problem. We conclude that deep convection caused enhanced mercury wet deposition in the southeastern US.
Peng Zhang and Yanxu Zhang
Geosci. Model Dev., 15, 3587–3601, https://doi.org/10.5194/gmd-15-3587-2022, https://doi.org/10.5194/gmd-15-3587-2022, 2022
Short summary
Short summary
Mercury is a global pollutant that can be transported over long distance through the atmosphere. We develop a new online global model for atmospheric mercury. The model reproduces the observed global atmospheric mercury concentrations and deposition distributions by simulating the emissions, transport, and physicochemical processes of atmospheric mercury. And we find that the seasonal variations of atmospheric Hg are the result of multiple processes and have obvious regional characteristics.
Ruochong Xu, Joel A. Thornton, Ben H. Lee, Yanxu Zhang, Lyatt Jaeglé, Felipe D. Lopez-Hilfiker, Pekka Rantala, and Tuukka Petäjä
Atmos. Chem. Phys., 22, 5477–5494, https://doi.org/10.5194/acp-22-5477-2022, https://doi.org/10.5194/acp-22-5477-2022, 2022
Short summary
Short summary
Monoterpenes are emitted into the atmosphere by vegetation and by the use of certain consumer products. Reactions of monoterpenes in the atmosphere lead to low-volatility products that condense to grow particulate matter or participate in new particle formation and, thus, affect air quality and climate. We use a model of atmospheric chemistry and transport to evaluate the global-scale importance of recent updates to our understanding of monoterpene chemistry in particle formation and growth.
Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
Short summary
Short summary
We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
Qi En Zhong, Chunlei Cheng, Zaihua Wang, Lei Li, Mei Li, Dafeng Ge, Lei Wang, Yuanyuan Li, Wei Nie, Xuguang Chi, Aijun Ding, Suxia Yang, Duohong Chen, and Zhen Zhou
Atmos. Chem. Phys., 21, 17953–17967, https://doi.org/10.5194/acp-21-17953-2021, https://doi.org/10.5194/acp-21-17953-2021, 2021
Short summary
Short summary
Particulate amines play important roles in new particle formation, aerosol acidity, and hygroscopicity. Most of the field observations did not distinguish the different behavior of each type amine under the same ambient influencing factors. In this study, two amine-containing single particles exhibited different mixing states and disparate enrichment of secondary organics, which provide insight into the discriminated fates of organics during the formation and evolution processes.
Yuliang Liu, Wei Nie, Yuanyuan Li, Dafeng Ge, Chong Liu, Zhengning Xu, Liangduo Chen, Tianyi Wang, Lei Wang, Peng Sun, Ximeng Qi, Jiaping Wang, Zheng Xu, Jian Yuan, Chao Yan, Yanjun Zhang, Dandan Huang, Zhe Wang, Neil M. Donahue, Douglas Worsnop, Xuguang Chi, Mikael Ehn, and Aijun Ding
Atmos. Chem. Phys., 21, 14789–14814, https://doi.org/10.5194/acp-21-14789-2021, https://doi.org/10.5194/acp-21-14789-2021, 2021
Short summary
Short summary
Oxygenated organic molecules (OOMs) are crucial intermediates linking volatile organic compounds to secondary organic aerosols. Using nitrate time-of-flight chemical ionization mass spectrometry in eastern China, we performed positive matrix factorization (PMF) on binned OOM mass spectra. We reconstructed over 1000 molecules from 14 derived PMF factors and identified about 72 % of the observed OOMs as organic nitrates, highlighting the decisive role of NOx in OOM formation in populated areas.
Markku Kulmala, Tom V. Kokkonen, Juha Pekkanen, Sami Paatero, Tuukka Petäjä, Veli-Matti Kerminen, and Aijun Ding
Atmos. Chem. Phys., 21, 8313–8322, https://doi.org/10.5194/acp-21-8313-2021, https://doi.org/10.5194/acp-21-8313-2021, 2021
Short summary
Short summary
The eastern part of China as a whole is practically a gigacity with 650 million inhabitants. The gigacity, with its emissions, processes in the pollution cocktail and numerous feedbacks and interactions, has a crucial and big impact on regional air quality and on global climate. A large-scale research and innovation program is needed to meet the interlinked grand challenges in this gigacity and to serve as a platform for finding pathways for sustainable development of the globe.
Yanxu Zhang, Xingpei Ye, Shibao Wang, Xiaojing He, Lingyao Dong, Ning Zhang, Haikun Wang, Zhongrui Wang, Yun Ma, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Ling Zhang, and Yongle Xiao
Atmos. Chem. Phys., 21, 2917–2929, https://doi.org/10.5194/acp-21-2917-2021, https://doi.org/10.5194/acp-21-2917-2021, 2021
Short summary
Short summary
Urban air quality varies drastically at street scale, but traditional methods are too coarse to resolve it. We develop a 10 m resolution air quality model and apply it for traffic-related carbon monoxide air quality in Nanjing megacity. The model reveals a detailed geographical dispersion pattern of air pollution in and out of the road network and agrees well with a validation dataset. The model can be a vigorous part of the smart city system and inform urban planning and air quality management.
Ying Jiang, Likun Xue, Rongrong Gu, Mengwei Jia, Yingnan Zhang, Liang Wen, Penggang Zheng, Tianshu Chen, Hongyong Li, Ye Shan, Yong Zhao, Zhaoxin Guo, Yujian Bi, Hengde Liu, Aijun Ding, Qingzhu Zhang, and Wenxing Wang
Atmos. Chem. Phys., 20, 12115–12131, https://doi.org/10.5194/acp-20-12115-2020, https://doi.org/10.5194/acp-20-12115-2020, 2020
Short summary
Short summary
We analyzed the characteristics and sources of HONO in the upper boundary layer and lower free troposphere in the North China Plain, based on the field measurements at Mount Tai. Higher-than-expected levels and broad daytime peaks of HONO were observed. Without presence of ground surfaces, aerosol surface plays a key role in the heterogeneous HONO formation at high altitudes. Models without additional HONO sources largely
underestimatedthe oxidation processes in the elevation atmospheres.
Cited articles
An, J. L., Zou, J., Wang, J., Lin., X., and Zhu, B.: Differences in ozone
photochemical characteristics between the megacity
Nanjing and its suburban surroundings, Yangtze River Delta, China, Environ.
Sci. Pollut. Res., 22, 19607–19617,
https://doi.org/10.1007/s11356-015-5177-0, 2015.
Apte, J. S., Kirchstetter, T. W., Reich, A. H., Deshpande, S. J., Kaushik,
G., Chel, A., Marshall, J. D., and Nazaroff, W. W.:
Concentrations of fine, ultrafine, and black carbon particles in
auto-rickshaws in New Delhi, India, Atmos. Environ., 45,
4470–4480, https://doi.org/10.1016/j.atmosenv.2011.05.028,
2011.
Apte, J. S., Messier, K. P., Gani, S., Brauer, M., Kirchstetter, T. W.,
Lunden, M. M., Marshall, J. D., Portier, C. J., Vermeulen,
R. C. H., and Hamburg, S. P.: High-resolution air pollution mapping with
google street view cars: exploiting big data,
Environ. Sci. Technol., 51, 6999–7008, https://doi.org/10.1021/acs.est.7b00891, 2017.
Awang, N. R., Ramli, N. A., Yahaya, A. S., and Elbayoumi, M.: High nighttime
ground-level ozone concentrations in
Kemaman: NO and NO2 concentrations attributions, Aerosol Air Qual.
Res., 15, 1357–1366, https://doi.org/10.4209/aaqr.2015.01.0031, 2015.
Bao, R. and Zhang, A.: Does lockdown reduce air pollution? Evidence from 44
cities in northern China, Sci. Total Environ.,
139052, https://doi.org/10.1016/j.scitotenv.2020.139052, 2020.
Bart, E., Jan P., Martine, V. P., Nico, B., and Arnout, S.: The aeroflex: a
bicycle for mobile air quality measurements,
Sensors, 13, 221–240, https://doi.org/10.3390/s130100221,
2012.
Boogaard, H., Kos, G. P. A., Weijers, E. P., Janssen, N. A. H., Fischer, P.
H., Van der Zee, S. C., De Hartog, J. J., and Hoek,
G.: Contrast in air pollution components between major streets and
background locations: Particulate matter mass, black
carbon, elemental composition, nitrogen oxide and ultrafine particle number,
Atmos. Environ., 45, 650–658,
https://doi.org/10.1016/j.atmosenv.2010.10.033, 2010.
Borrego, C., Coutinho, M., Costa, A. M., Ginja, J., Ribeiro, C., Monteiro,
A., Ribeiro, I., Valente, J., Amorim, J. H., Martins,
H., Lopes, D., and Miranda, A. I.: Challenges for a new air quality
directive: the role of monitoring and modelling
techniques, Urban Clim., 14, 328–341, https://doi.org/10.1016/j.uclim.2014.06.007, 2015.
Bossche, J. V. D., Peters, J., Verwaeren, J., Botteldooren, D., Theunis, J.,
and Baets, B. D.: Mobile monitoring for mapping
spatial variation in urban air quality: Development and validation of a
methodology based on an extensive dataset, Atmos.
Environ., 105, 148–161, https://doi.org/10.1016/j.atmosenv.2015.01.017, 2015.
Bureau Statistics of Nanjing Municipal: Nangjing Statistical Yearbook,
available at: http://tjj.nanjing.gov.cn/bmfw/njsj/ (last access: 8 November 2020), 2019.
Castell, N., Dauge, F. R., Schneider, P., Vogt, M., Lerner, U., Fishbain,
B., Broday, D., and Bartonova, A.: Can commercial
low-cost sensor platforms contribute to air quality monitoring and exposure
estimates?, Environ. Int., 99, 293–302,
https://doi.org/10.1016/j.envint.2016.12.007, 2017.
Cavellin, L. D., Weichenthal, S., Tack, R., Ragettli, M. S., Smargiassi, A.,
and Hatzopoulou, M.: Investigating the use of
portable air pollution sensors to capture the spatial variability of
traffic-related air pollution, Environ. Sci. Technol., 50,
313–320, https://doi.org/10.1021/acs.est.5b04235, 2016.
Chatzidiakou, L., Krause, A., Popoola, O. A. M., Di Antonio, A., Kellaway, M., Han, Y., Squires, F. A., Wang, T., Zhang, H., Wang, Q., Fan, Y., Chen, S., Hu, M., Quint, J. K., Barratt, B., Kelly, F. J., Zhu, T., and Jones, R. L.: Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments, Atmos. Meas. Tech., 12, 4643–4657, https://doi.org/10.5194/amt-12-4643-2019, 2019.
Ding, A. J., Fu, C. B., Yang, X. Q., Sun, J. N., Zheng, L. F., Xie, Y. N., Herrmann, E., Nie, W., Petäjä, T., Kerminen, V.-M., and Kulmala, M.: Ozone and fine particle in the western Yangtze River Delta: an overview of 1 yr data at the SORPES station, Atmos. Chem. Phys., 13, 5813–5830, https://doi.org/10.5194/acp-13-5813-2013, 2013.
Esposito, E., Vito, S. D., Salvato, M., Fattoruso, G., Bright, V., Jones, R.
L., and Popoola, O.: Stochastic Comparison of Machine Learning Approaches to Calibration of Mobile Air Quality Monitors, in: Sensors, CNS 2016, Lecture Notes in Electrical Engineering, edited by: Andò, B., Baldini, F., Di Natale, C., Marrazza, G., Siciliano, P., vol 431, Springer, Cham, https://doi.org/10.1007/978-3-319-55077-0_38, 2018.
Farrell, W. J., Cavellin, L. D., Weichenthal, S., Goldberg, M., and
Hatzopoulou, M.: Capturing the urban canyon effect on
particle number concentrations across a large road network using spatial
analysis tools, Build. Environ., 92, 328–334,
https://doi.org/10.1016/j.buildenv.2015.05.004, 2015.
Fu, T. M., Zheng, Y., Paulot, F., and Mao, J.: Positive but variable
sensitivity of August surface ozone to large-scale warming
in the southeast United States, Nat. Clim. Change, 5, 454–458, https://doi.org/10.1038/nclimate2567, 2015.
Gately, C. K., Hutyra, L. R., Peterson, S., and Wing, I. S.: Urban emissions
hotspots: Quantifying vehicle congestion and air
pollution using mobile phone GPS data, Environ. Pollut., 229, 496–504,
https://doi.org/10.1016/j.envpol.2017.05.091,
2017.
Guevara, M., Jorba, O., Soret, A., Petetin, H., Bowdalo, D., Serradell, K., Tena, C., Denier van der Gon, H., Kuenen, J., Peuch, V.-H., and Pérez García-Pando, C.: Time-resolved emission reductions for atmospheric chemistry modelling in Europe during the COVID-19 lockdowns, Atmos. Chem. Phys., 21, 773–797, https://doi.org/10.5194/acp-21-773-2021, 2021.
Hagan, D. H., Gani, S., Bhandari, S., Patel, K., Habib, G., Apte, J. S.,
Ruiz, L. H., and Kroll, J. H.: Inferring aerosol sources
from low-cost air quality sensor measurements: a case study in Delhi, India,
Environ. Sci. Tech. Let., 6, 467–472,
https://doi.org/10.1021/acs.estlett.9b00393, 2019.
Hasenfratz, D., Saukh, O., Walser, C., Hueglin, C., Fierz, M., Arn, T.,
Beutel, J., and Thiele, L.: Deriving high-resolution
urban air pollution maps using mobile sensor nodes, Pervasive Mob. Comput.,
16, 268–285,
https://doi.org/10.1016/j.pmcj.2014.11.008, 2015.
Herrmann, E., Ding, A. J., Petäjä, T., Yang, X. Q., Sun, J. N., Qi, X. M., Manninen, H., Hakala, J., Nieminen, T., Aalto, P. P., Kerminen, V.-M., Kulmala, M., and Fu, C. B.: New particle formation in the western Yangtze River Delta: first data from SORPES-station, Atmos. Chem. Phys. Discuss., 13, 1455–1488, https://doi.org/10.5194/acpd-13-1455-2013, 2013.
Hilker, N., Wang, J. M., Jeong, C.-H., Healy, R. M., Sofowote, U., Debosz, J., Su, Y., Noble, M., Munoz, A., Doerksen, G., White, L., Audette, C., Herod, D., Brook, J. R., and Evans, G. J.: Traffic-related air pollution near roadways: discerning local impacts from background, Atmos. Meas. Tech., 12, 5247–5261, https://doi.org/10.5194/amt-12-5247-2019, 2019.
Huang, X., Ding, A. J., Gao, J., Zheng, B., Zhou, D. R., Qi, X., Tang, R.,
Wang, J., Ren, C., Nie, W., Chi, X., Xu, Z., Chen,
L., Li, Y., Che, F., Pang, N., Wang, H. K., Tong, D., Qin, W., Cheng, W.,
Liu, W., Fu, Q., Liu, B., Chai, F. H., Davis, S. J.,
Zhang, Q., and He, K. B.: Enhanced secondary pollution offset reduction of
primary emissions during COVID-19
lockdown in China, Natl. Sci. Rev., 8, 1–9, https://doi.org/10.1093/nsr/nwaa137, 2021.
Isakov, V., Touma, J. S., and Khlystov, A.: A method of assessing air toxics
concentrations in urban areas using mobile
platform measurements, J. Air Waste Manage. Assoc., 57, 1286–1295,
https://doi.org/10.3155/1047-3289.57.11.1286,
2007.
Ivanovskaya, M., Gurlo, A., and Bogdanov, P.: Mechanism of O3 and
NO2 detection and selectivity of In2O3 sensors, Sensor
Actuat. B-Chem., 77, 264–267, https://doi.org/10.1016/S0925-4005(01)00708-0, 2001.
Johnson, N. E., Bonczak, B., and Kontokosta, C. E.: Using a gradient
boosting model to improve the performance of
low-cost aerosol monitors in a dense, heterogeneous urban environment,
Atmos. Environ., 184, 9–16,
https://doi.org/10.1016/j.atmosenv.2018.04.019, 2018.
Kaivonen, S. and Ngai, E.: Real-time air pollution monitoring with sensors
on city bus, Digit. Commun. Netw., 6, 23–30,
https://doi.org/10.1016/j.dcan.2019.03.003, 2020.
Karner, A. A., Eisinger, D. S., and Niemeier, D. A.: Near-roadway air
quality: synthesizing the findings from real-world data,
Environ. Sci. Technol., 44, 5334–5344, https://doi.org/10.1021/es100008x, 2010.
Kaur, S., Nieuwenhuijsen, M. J., and Colvile, R. N.: Fine particulate matter
and carbon monoxide exposure concentrations in
urban street transport microenvironments, Atmos. Environ., 41, 4781–4810,
https://doi.org/10.1016/j.atmosenv.2007.02.002, 2007.
Kerckhoffs, J., Hoek, G., Messier, K. P., Brunekreef, B., Meliefste, K.,
Klompmaker, J. O., and Vermeulen, R.: Comparison
of ultrafine particle and black carbon concentration predictions from a
mobile and short-term stationary land-use
regression model, Environ. Sci. Technol., 50, 12894–12902, https://doi.org/10.1021/acs.est.6b03476, 2016.
Kirchstetter, T. W., Singer, B. C., Harley, R. A., Kendall, G. R., and Chan,
W.: Impact of oxygenated gasoline use on
California light-duty vehicle emissions, Environ. Sci. Technol., 30,
661–670, https://doi.org/10.1021/es950406p, 1996.
Kizel, F., Etzion, Y., Shafran-Nathan, R., Levy, I., Fishbain, B.,
Bartonova, A., and Broday, D. M.: Node-to-node field calibration of wireless
distributed air pollution sensor network, Environ. Pollut., 233, 900–909,
https://doi.org/10.1016/j.envpol.2017.09.042, 2018.
Laughner, J. L., Zhu, Q., and Cohen, R. C.: The Berkeley High Resolution Tropospheric NO2 product, Earth Syst. Sci. Data, 10, 2069–2095, https://doi.org/10.5194/essd-10-2069-2018, 2018.
Li, M. J., Chen, D. S., Cheng, S. Y., Wang, F., Li, Y., Zhou, Y., and Lang,
J. L.: Optimizing emission inventory for chemical
transport models by using genetic algorithm, Atmos. Environ., 44,
3926–3934,
https://doi.org/10.1016/j.atmosenv.2010.07.010, 2010.
Li, Y., Lau, A. K. H., Fung, J. C. H., Zheng, J. Y., and Liu, S.: Importance
of NOx control for peak ozone reduction in the
Pearl River Delta region, J. Geophys. Res.-Atmos., 118, 9428–9443,
https://doi.org/10.1002/jgrd.50659, 2013.
Li, Z., Fung, J. C. H., and Lau, A. K. H.: High spatiotemporal
characterization of on-road PM2.5 concentrations in
high-density urban areas using mobile monitoring, Build. Environ., 143,
196–205,
https://doi.org/10.1016/j.buildenv.2018.07.014, 2018.
Lim, C. C., Kim, H., Vilcassim, M. J. R., Thurston, G. D., Gordon, T., Chen,
L. C., Lee, K., Heimbinder, M., and Kim, S.:
Mapping urban air quality using mobile sampling with low-cost sensors and
machine learning in Seoul, South Korea,
Environ. Int., 131, 105022, https://doi.org/10.1016/j.envint.2019.105022, 2019.
Liu, Y., Li, L., An, J., Huang, L., Yan, R., Huang, C., Wang, H., Wang, Q.,
Wang, M., and Zhang, W.: Estimation of biogenic
VOC emissions and its impact on ozone formation over the Yangtze River Delta
region, China, Atmos. Environ., 186,
113–128, https://doi.org/10.1016/j.atmosenv.2018.05.027, 2018.
Lösch, M., Baumbach, M., and Schütze, A.: Ozone detection in the
ppb-range with improved stability and reduced cross
sensitivity, Sensor Actuat. B-Chem., 130, 367–373, https://doi.org/10.1016/j.snb.2007.09.033, 2008.
Maag, B., Zhou, Z., and Thiele, L.: A Survey on Sensor Calibration in Air
Pollution Monitoring Deployments, IEEE Internet
Things, 5, 4857–4870, https://doi.org/10.1109/JIOT.2018.2853660, 2018.
McClurkin, J. D., Maier, D. E., and Ileleji, K. E.: Half-life time of ozone
as a function of air movement and conditions in a
sealed container, J. Stored Prod. Res., 55, 41–47, https://doi.org/10.1016/j.jspr.2013.07.006, 2013.
Miller, D. J., Actkinson, B., Padilla, L., Griffin, R. J., Moore, K., Lewis,
P. G. T., Gardner-Frolick, R., Craft, E., Portier, C. J.,
Hamburg, S. P., and Alvarez, R.A.: Characterizing elevated urban air
pollutant spatial patterns with mobile monitoring in
Houston, Texas, Environ. Sci. Technol., 54, 2133–2142, https://doi.org/10.1021/acs.est.9b05523, 2020.
Miskell, G., Salmond, J., and Williams, D. E.: A solution to the problem of
calibration of low-cost air quality measurement
sensors in networks, ACS Sens., 3, 832–843, https://doi.org/10.1021/acssensors.8b00074, 2018.
O'Keeffe, K. P., Anjomshoaa, A., Strogatz, S. H., Santi, P., and Ratti C.:
Quantifying the sensing power of vehicle fleets,
P. Natl. Acad. Sci. USA, 116, 12752–12757, https://doi.org/10.1073/pnas.1821667116, 2019.
OpenStreetMap contributors: Roads and land use data of Nanjing, available at: https://download.geofabrik.de/asia/china.html and https://www.openstreetmap.org, last access: 2 October 2020.
Padro-Martinez, L. T., Patton, A. P., Trull, J. B., Zamore, W., Brugge, D.,
and Durant, J. L.: Mobile monitoring of particle
number concentration and other traffic-related air pollutants in a
near-highway neighborhood over the course of a year,
Atmos. Environ., 61, 253–264, https://doi.org/10.1016/j.atmosenv.2012.06.088, 2012.
Peters, J., Theunis, J., Van Poppel, M., and Berghmans, P.: Monitoring
PM10 and ultrafine particles in urban environments
using mobile measurements, Aerosol Air Qual. Res., 13, 509–522, https://doi.org/10.4209/aaqr.2012.06.0152, 2013.
Poppel, M. V., Peters, J., and Bleux, N.: Methodology for setup and data
processing of mobile air quality measurements to
assess the spatial variability of concentrations in urban environments,
Environ. Pollut., 183, 224–233,
https://doi.org/10.1016/j.envpol.2013.02.020, 2013.
Popoola, O. A. M., Stewart, G. B., Mead, M. I., and Jones, R. L.:
Development of a baseline-temperature correction methodology for
electrochemical sensors and its implications for long-term stability, Atmos.
Environ., 147, 330–343, https://doi.org/10.1016/j.atmosenv.2016.10.024, 2016.
Qin, X., Hou, L., Gao, J., and Si, S.: The evaluation and optimization of
calibration methods for low-cost particulate matter
sensors: Inter-comparison between fixed and mobile methods, Sci. Total
Environ., 715, 136791,
https://doi.org/10.1016/j.scitotenv.2020.136791, 2020.
Qin, Y., Tonnesen, G. S., and Wang, Z.: Weekend/weekday differences of
ozone, NOx, CO, VOCs, PM10 and the light scatter
during ozone season in southern California, Atmos. Environ., 38,
3069–3087,
https://doi.org/10.1016/j.atmosenv.2004.01.035, 2004.
Reddy, B. S. K., Kumar, K. R., Balakrishnaiah, G., Gopal, K. R., Reddy,
R. R., Ahammed, Y. N., Narasimhulu, K., Reddy, L.
S. S., and Lal, S.: Observational studies on the variations in surface ozone
concentration at Anantapur in southern India,
Atmos. Res., 98, 125–139, https://doi.org/10.1016/j.atmosres.2010.06.008, 2010.
Ribet, F., Pietro, L. D., Roxhed, N., and Stemme, G.: Gas diffusion and
evaporation control using EWOD actuation of ionic
liquid microdroplets for gas sensing applications, Sensor Actuat. B-Chem.,
267, 647–654,
https://doi.org/10.1016/j.snb.2018.04.076, 2018.
Romer, P. S., Duffey, K. C., Wooldridge, P. J., Allen, H. M., Ayres, B. R., Brown, S. S., Brune, W. H., Crounse, J. D., de Gouw, J., Draper, D. C., Feiner, P. A., Fry, J. L., Goldstein, A. H., Koss, A., Misztal, P. K., Nguyen, T. B., Olson, K., Teng, A. P., Wennberg, P. O., Wild, R. J., Zhang, L., and Cohen, R. C.: The lifetime of nitrogen oxides in an isoprene-dominated forest, Atmos. Chem. Phys., 16, 7623–7637, https://doi.org/10.5194/acp-16-7623-2016, 2016.
Sahanavin, N., Prueksasit, T., and Tantrakarnapa, K.: Relationship between PM10
and PM2.5 levels in high-traffic area determined using path analysis and linear
regression, J. Environ. Sci., 69, 105–114, https://doi.org/10.1016/j.jes.2017.01.017, 2018
Sharma, S., Sharma, P., Khare, M., and Kwatra, S.: Statistical behavior of
ozone in urban environment, Sust. Environ. Res.,
26, 142–148, https://doi.org/10.1016/j.serj.2016.04.006,
2016.
SM, S. N., Pavan, R. Y., Narayana, M. V., Seema, K., and Pooja, R.: Mobile
monitoring of air pollution using low cost
sensors to visualize spatio-temporal variation of pollutants at urban
hotspots, Sustain. Cities Soc., 44, 520–535,
https://doi.org/10.1016/j.scs.2018.10.006, 2019.
Snyder, E. G., Watkins, T. H., Solomon, P. A., Thoma, E. D., Williams, R.
W., Hagler, G. S. W., Shelow, D., Hindin, D. A.,
Kilaru, V. J., and Preuss, P. W.: The changing paradigm of air pollution
monitoring, Environ. Sci. Technol., 47, 11369–11377, https://doi.org/10.1021/es4022602, 2013.
Spinelle, L., Gerboles, M., Villani, M., Aleixandre, M., and Bonavitacola,
F.: Field calibration of a cluster of low-cost
commercially available sensors for air quality monitoring. Part B: NO, CO
and CO2, Sensor Actuat. B-Chem., 238,
706–715, https://doi.org/10.1016/j.snb.2016.07.036, 2017.
Tan, P. H., Chou, C., Liang, J. Y., Chou, C. C. K., and Shiu, C. J.: Air
pollution “holiday effect” resulting from the Chinese
New Year, Atmos. Environ., 43, 2114–2124, https://doi.org/10.1016/j.atmosenv.2009.01.037, 2009.
Targino, A. C., Gibson, M. D., Krecl, P., Rodrigues, M. V. C., Santos, M. M.
D., and Corrêa, M. D. P.: Hotspots of black
carbon and PM2.5 in an urban area and relationships to traffic
characteristics, Environ. Pollut., 218, 475–486,
https://doi.org/10.1016/j.envpol.2016.07.027, 2016.
Vito, S. D., Esposito, E., Salvato, M., Popoola, O., Formisano, F., Jones,
R., and Francia, G. D.: Calibrating chemical
multisensory devices for real world applications: An in-depth comparison of
quantitative machine learning approaches,
Sensor Actuat. B-Chem., 255, 1191–1210, https://doi.org/10.1016/j.snb.2017.07.155, 2018.
Wang, Y. H., Hu, B., Ji, D. S., Liu, Z. R., Tang, G. Q., Xin, J. Y., Zhang, H. X., Song, T., Wang, L. L., Gao, W. K., Wang, X. K., and Wang, Y. S.: Ozone weekend effects in the Beijing–Tianjin–Hebei metropolitan area, China, Atmos. Chem. Phys., 14, 2419–2429, https://doi.org/10.5194/acp-14-2419-2014, 2014.
Wei, P., Ning, Z., Ye, S., Sun, L., Yang, F., Wong, K. C., Westerdahl, D.,
Louie, P.: Impact analysis of temperature and
humidity conditions on electrochemical sensor response in ambient air
quality monitoring, Sensors-Basel,
18, 1–16, https://doi.org/10.3390/s18020059, 2018.
Weissert, L., Alberti, K., Miles, E., Miskell, G., Feenstra, B., Henshaw, G.
S., Papapostolou, V., Patel, H., Polidori, A.,
Salmond, J. A., and Williams, D. E.: Low-cost sensor networks and land-use
regression: Interpolating nitrogen dioxide
concentration at high temporal and spatial resolution in Southern
California, Atmos. Environ., 223, 117287,
https://doi.org/10.1016/j.atmosenv.2020.117287, 2020.
World Health Organization (WHO): WHO Global Urban Ambient Air Pollution
Database, available at:
https://www.who.int/phe/health_topics/outdoorair/databases/cities/en/ (last access: 4 May 2020), 2016.
World Health Organization (WHO): 9 out of 10 People Worldwide Breathe
Polluted Air, but More Countries Are
Taking Action, available at:
https://www.who.int/news/item/02-05-2018-9-out-of-10-people-
worldwide-breathe-polluted-air-but-more-countries-are-taking-action,
last accessed: 16 September 2018.
Wu, Y., Zhang, S., Hao, J. M., Liu, H., Wu, X., Hu, J. N., Walsh, M. P.,
Wallington, T. J., Zhang, K. M., and Stevanovic, S.:
On-road vehicle emissions and their control in China: a review and outlook,
Sci. Total Environ., 574, 332–349,
https://doi.org/10.1016/j.scitotenv.2016.09.040, 2017.
Xie, M., Zhu, K., Wang, T., Chen, P., Han, Y., Li, S., Zhuang, B. L., and
Shu, L.: Temporal characterization and regional
contribution to O3 and NOx at an urban and a suburban site in Nanjing,
China, Sci. Total Environ., 551–552, 533–545,
https://doi.org/10.1016/j.scitotenv.2016.02.047, 2016.
Xu, H., Bechle, M. J., Wang, M., Szpiro, A. A., Vedal, S., Bai, Y. Q., and
Marshall, J. D.: National PM2.5 and NO2 exposure
models for China based on land use regression, satellite measurements, and
universal kriging, Sci. Total Environ., 655,
423–433, https://doi.org/10.1016/j.scitotenv.2018.11.125,
2019.
Xu, Z., Huang, X., Nie, W., Chi, X., Xu, Z., Zheng, L., Sun, P., and Ding,
A. J.: Influence of synoptic condition and holiday
effects on VOCs and ozone production in the Yangtze River Delta region,
China, Atmos. Environ., 168, 112–124,
https://doi.org/10.1016/j.atmosenv.2017.08.035, 2017.
Yang, S., Wu, J., Du, Y., He, Y., and Chen, X.: Ensemble learning for
short-term traffic prediction based on gradient boosting
machine, J. Sensors, 2017, 1–15, https://doi.org/10.1155/2017/7074143, 2017.
Zhang, R., Zhang, Y., Lin, H., Feng, X., Fu, T., and Wang, Y.: NOx emission
reduction and recovery during
COVID-19 in east China, Atmosphere, 11, 433, https://doi.org/10.3390/atmos11040433, 2020.
Zhang, Y., Ye, X., Wang, S., He, X., Dong, L., Zhang, N., Wang, H., Wang, Z., Ma, Y., Wang, L., Chi, X., Ding, A., Yao, M., Li, Y., Li, Q., Zhang, L., and Xiao, Y.: Large-eddy simulation of traffic-related air pollution at a very high resolution in a mega-city: evaluation against mobile sensors and insights for influencing factors, Atmos. Chem. Phys., 21, 2917–2929, https://doi.org/10.5194/acp-21-2917-2021, 2021.
Zhao, Y., Qiu, L. P., Xu, R. Y., Xie, F. J., Zhang, Q., Yu, Y. Y., Nielsen, C. P., Qin, H. X., Wang, H. K., Wu, X. C., Li, W. Q., and Zhang, J.: Advantages of a city-scale emission inventory for urban air quality research and policy: the case of Nanjing, a typical industrial city in the Yangtze River Delta, China, Atmos. Chem. Phys., 15, 12623–12644, https://doi.org/10.5194/acp-15-12623-2015, 2015.
Zheng, B., Huo, H., Zhang, Q., Yao, Z. L., Wang, X. T., Yang, X. F., Liu, H., and He, K. B.: High-resolution mapping of vehicle emissions in China in 2008, Atmos. Chem. Phys., 14, 9787–9805, https://doi.org/10.5194/acp-14-9787-2014, 2014.
Zhu, Y. F., Pudota, J., Collins, D., Allen, D., Clements, A., DenBleyker,
A., Fraser, M., Jia, Y. L., McDonald-Buller, E., and
Michel, E.: Air pollutant concentrations near three Texas roadways, Part I:
Ultrafine particles, Atmos. Environ., 43,
4513–4522, https://doi.org/10.1016/j.atmosenv.2009.04.018,
2009.
Zou, C., Wu, L., Li, X., Yuan, Y., Jing, B., and Mao, H. J.: Relationship
between traffic flow and temporal and spatial
variations of NO2 and CO in Nanjing, Acta Sci. Circumstantiae, 37,
3894–3905,
https://doi.org/10.13671/j.hjkxxb.2017.0374, 2017 (in Chinese).
Short summary
Mobile monitoring with low-cost sensors is a promising approach to garner high-spatial-resolution observations representative of the community scale. We develop a grid analysis method to obtain 50 m resolution maps of major air pollutants (CO, NO2, and O3) based on GIS technology. Our results demonstrate the sensing power of mobile monitoring for urban air pollution, which provides detailed information for source attribution and accurate traceability at the urban micro-scale.
Mobile monitoring with low-cost sensors is a promising approach to garner...
Altmetrics
Final-revised paper
Preprint