100 citations as recorded by crossref.

1. Urban Air Pollution Mapping Using Fleet Vehicles as Mobile Monitors and Machine Learning B. Zhao et al. 10.1021/acs.est.0c08034
2. High-resolution urban air pollution mapping J. Apte & C. Manchanda 10.1126/science.adq3678
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4. Characterization of Spatial Air Pollution Patterns Near a Large Railyard Area in Atlanta, Georgia H. Brantley et al. 10.3390/ijerph16040535
5. High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data J. Apte et al. 10.1021/acs.est.7b00891
6. A mobile car monitoring system as a supplementary tool for air quality monitoring in urban and rural environments: the case study from Poland M. Maslouski et al. 10.1038/s41598-023-43095-w
7. Advancements in Mobile-Based Air Pollution Detection: From Literature Review to Practical Implementation S. Sladojevic et al. 10.1155/2024/4895068
8. Continuous atmospheric in-situ measurements of the CH4/CO ratio at the Mt. Cimone station (Italy, 2165 m a.s.l.) and their possible use for estimating regional CH4 emissions C. Fratticioli et al. 10.1016/j.envres.2023.116343
9. Mobile and Fixed-Site Measurements To Identify Spatial Distributions of Traffic-Related Pollution Sources in Los Angeles M. Tessum et al. 10.1021/acs.est.7b04889
10. Spatial variation of fine particulate matter levels in Nairobi before and during the COVID-19 curfew: implications for environmental justice P. deSouza et al. 10.1088/2515-7620/ac1214
11. On-highway vehicle emission factors, and spatial patterns, based on mobile monitoring and absolute principal component score Y. Wen et al. 10.1016/j.scitotenv.2019.04.185
12. Urbanization and regional air pollution across South Asian developing countries – A nationwide land use regression for ambient PM2.5 assessment in Pakistan Y. Shi et al. 10.1016/j.envpol.2020.115145
13. High Resolution On-Road Air Pollution Using a Large Taxi-Based Mobile Sensor Network Y. Sun et al. 10.3390/s22166005
14. Commuter exposure to black carbon particles on diesel buses, on bicycles and on foot: a case study in a Brazilian city A. Targino et al. 10.1007/s11356-017-0517-x
15. Improving emissions inputs via mobile measurements to estimate fine-scale Black Carbon monthly concentrations through geostatistical space-time data fusion A. Valencia et al. 10.1016/j.scitotenv.2021.148378
16. High spatiotemporal characterization of on-road PM2.5 concentrations in high-density urban areas using mobile monitoring Z. Li et al. 10.1016/j.buildenv.2018.07.014
17. SIBaR: a new method for background quantification and removal from mobile air pollution measurements B. Actkinson et al. 10.5194/amt-14-5809-2021
18. Near-road measurements for nitrogen dioxide and its association with traffic exposure zones L. Smith et al. 10.1016/j.apr.2015.06.005
19. Modelling nationwide spatial variation of ultrafine particles based on mobile monitoring J. Kerckhoffs et al. 10.1016/j.envint.2021.106569
20. Evaluating the Meteorological Effects on the Urban Form–Air Quality Relationship Using Mobile Monitoring Y. Tian et al. 10.1021/acs.est.1c04854
21. Evaluation of the Relationship between Meteorological Variables and NOx Emission Factors Based on Plume-Chasing Measurements S. Xiang et al. 10.1021/acsestengg.2c00317
22. Mobile measurement background quantification methods for determining local traffic emissions and background source contributions to ammonia W. Pu et al. 10.1016/j.atmosenv.2024.120523
23. Comparison of modeled traffic exposure zones using on–road air pollution measurements M. Shaibal et al. 10.5094/APR.2015.010
24. Predicting citywide distribution of air pollution using mobile monitoring and three-dimensional urban structure L. Cummings et al. 10.1016/j.scs.2021.103510
25. Baseline drift estimation for air quality data using quantile trend filtering H. Brantley et al. 10.1214/19-AOAS1318
26. Analysing and predicting the fine-scale distribution of traffic particulate matter in urban nonmotorized lanes by using wavelet transform and random forest methods B. Luo et al. 10.1007/s00477-023-02411-6
27. Reducing the Influence of Environmental Factors on Performance of a Diffusion-Based Personal Exposure Kit H. Zong et al. 10.3390/s21144637
28. Prediction of Short-Term Ultrafine Particle Exposures Using Real-Time Street-Level Images Paired with Air Quality Measurements J. Xu et al. 10.1021/acs.est.2c03193
29. Investigating the influence of urban land use and landscape pattern on PM2.5 spatial variation using mobile monitoring and WUDAPT Y. Shi et al. 10.1016/j.landurbplan.2019.04.004
30. Characterizing spatial variations of city-wide elevated PM10 and PM2.5 concentrations using taxi-based mobile monitoring Y. Yu et al. 10.1016/j.scitotenv.2022.154478
31. Spatially dense air pollutant sampling: Implications of spatial variability on the representativeness of stationary air pollutant monitors H. Li et al. 10.1016/j.aeaoa.2019.100012
32. Characterizing spatiotemporal distributions of black carbon and PM2.5 at a toll station: Observations on manual and electronic toll collection lanes Z. Luo et al. 10.1016/j.buildenv.2021.107933
33. Overestimation of on-road air quality surveying data measured with a mobile laboratory caused by exhaust plumes of a vehicle ahead in dense traffic areas S. Woo et al. 10.1016/j.envpol.2016.08.065
34. Spatiotemporal correlation of urban pollutants by long-term measurements on a mobile observation platform S. Crocchianti et al. 10.1016/j.envpol.2020.115645
35. Automated identification of local contamination in remote atmospheric composition time series I. Beck et al. 10.5194/amt-15-4195-2022
36. Performance of Vehicle Add-on Mobile Monitoring System PM2.5 measurements during wildland fire episodes A. Bittner et al. 10.1039/D3EA00170A
37. Mobile air quality monitoring and comparison to fixed monitoring sites for instrument performance assessment A. Whitehill et al. 10.5194/amt-17-2991-2024
38. Comparison of Ultrafine Particle and Black Carbon Concentration Predictions from a Mobile and Short-Term Stationary Land-Use Regression Model J. Kerckhoffs et al. 10.1021/acs.est.6b03476
39. On-Road Air Quality Associated with Traffic Composition and Street-Canyon Ventilation: Mobile Monitoring and CFD Modeling K. Kwak et al. 10.3390/atmos9030092
40. Field Assessment of the Village Green Project: An Autonomous Community Air Quality Monitoring System W. Jiao et al. 10.1021/acs.est.5b01245
41. Street View Imagery (SVI) in the Built Environment: A Theoretical and Systematic Review Y. Li et al. 10.3390/buildings12081167
42. Development of urban air monitoring with high spatial resolution using mobile vehicle sensors K. Yeom 10.1007/s10661-021-09139-2
43. Improving NO2 prediction by integrating tree diversity, urban form, and scale sensitivity through mobile monitoring Y. Tian et al. 10.1016/j.apgeog.2023.102943
44. Integration of air pollution data collected by mobile measurement to derive a preliminary spatiotemporal air pollution profile from two neighboring German-Czech border villages X. Liu et al. 10.1016/j.scitotenv.2020.137632
45. Ammonia and methane dairy emission plumes in the San Joaquin Valley of California from individual feedlot to regional scales D. Miller et al. 10.1002/2015JD023241
46. Real-time particle monitoring of pesticide drift from an axial fan airblast orchard sprayer M. Blanco et al. 10.1038/s41370-018-0090-5
47. Analysis of mobile monitoring data from the microAeth® MA200 for measuring changes in black carbon on the roadside in Augsburg X. Liu et al. 10.5194/amt-14-5139-2021
48. Mitigating air and noise pollution through highway capping: The Bundang-Suseo Highway Cap Project case study K. Park & J. Lee 10.1016/j.envpol.2024.123620
49. Mobile-platform measurement of air pollutant concentrations in California: performance assessment, statistical methods for evaluating spatial variations, and spatial representativeness P. Solomon et al. 10.5194/amt-13-3277-2020
50. New methods to derive street-scale spatial patterns of air pollution from mobile monitoring L. Padilla et al. 10.1016/j.atmosenv.2021.118851
51. Spatiotemporal Characteristics and Driving Factors of Black Carbon in Augsburg, Germany: Combination of Mobile Monitoring and Street View Images X. Liu et al. 10.1021/acs.est.0c04776
52. The Impact of Traffic and Meteorology on Urban Particle Mass and Particle Number Concentrations: Student-Led Studies Using Mobile Measurements before, during, and after the COVID-19 Pandemic Lockdowns O. Klemm et al. 10.3390/atmos13010062
53. Methane mapping, emission quantification, and attribution in two European cities: Utrecht (NL) and Hamburg (DE) H. Maazallahi et al. 10.5194/acp-20-14717-2020
54. Mobile monitoring for mapping spatial variation in urban air quality: Development and validation of a methodology based on an extensive dataset J. Van den Bossche et al. 10.1016/j.atmosenv.2015.01.017
55. Traffic-related air pollution near roadways: discerning local impacts from background N. Hilker et al. 10.5194/amt-12-5247-2019
56. Evaluating the Performance of Low-Cost PM2.5 Sensors in Mobile Settings P. deSouza et al. 10.1021/acs.est.3c04843
57. City Scanner: Building and Scheduling a Mobile Sensing Platform for Smart City Services A. Anjomshoaa et al. 10.1109/JIOT.2018.2839058
58. Determination of local traffic emission and non-local background source contribution to on-road air pollution using fixed-route mobile air sensor network P. Wei et al. 10.1016/j.envpol.2021.118055
59. Adapting Public Annotated Data Sets and Low-Quality Dash Cameras for Spatiotemporal Estimation of Traffic-Related Air Pollution: A Transfer-Learning Approach Y. Fei et al. 10.1061/JCCEE5.CPENG-5667
60. Mobile Monitoring of Air Pollution Reveals Spatial and Temporal Variation in an Urban Landscape L. Cummings et al. 10.3389/fbuil.2021.648620
61. Comparison of Mobile and Fixed-Site Black Carbon Measurements for High-Resolution Urban Pollution Mapping S. Chambliss et al. 10.1021/acs.est.0c01409
62. Underestimated ammonia vehicular emissions in metropolitan city revealed by on-road mobile measurement C. Gu et al. 10.1088/1748-9326/acf94a
63. Smartphone Case-Based Gas Sensing Platform for On-site Acetone Tracking C. Xue et al. 10.1021/acssensors.2c00603
64. Low-power, open-path mobile sensing platform for high-resolution measurements of greenhouse gases and air pollutants L. Tao et al. 10.1007/s00340-015-6069-1
65. Use of mobile and passive badge air monitoring data for NOX and ozone air pollution spatial exposure prediction models W. Xu et al. 10.1038/jes.2016.9
66. Integrated Mobile Laboratory for Air Pollution Assessment: Literature Review and cc-TrAIRer Design C. Boanini et al. 10.3390/atmos12081004
67. Mobile measurements of atmospheric pollutant concentrations in the pollutant plume of BER airport L. Gerling & S. Weber 10.1016/j.atmosenv.2023.119770
68. Characterizing the Spatial Variation of Air Pollutants and the Contributions of High Emitting Vehicles in Pittsburgh, PA Y. Tan et al. 10.1021/es5034074
69. Bus commuter exposure and the impact of switching from diesel to biodiesel for routes of complex urban geometry A. Targino et al. 10.1016/j.envpol.2020.114601
70. A spatial land use clustering framework for investigating the role of land use in mediating the effect of meteorology on urban air quality A. Montazeri et al. 10.1016/j.aeaoa.2021.100126
71. Urban land use regression models: can temporal deconvolution of traffic pollution measurements extend the urban LUR to suburban areas? K. Shairsingh et al. 10.1016/j.atmosenv.2018.10.013
72. Real-Time Monitoring of Spray Drift from Three Different Orchard Sprayers M. Blanco et al. 10.1016/j.chemosphere.2019.01.092
73. Inferred vehicular emissions at a near-road site: Impacts of COVID-19 restrictions, traffic patterns, and ambient air temperature D. Hall-Quinlan et al. 10.1016/j.atmosenv.2023.119649
74. Integrating Mobile and Fixed-Site Black Carbon Measurements to Bridge Spatiotemporal Gaps in Urban Air Quality C. Manchanda et al. 10.1021/acs.est.3c10829
75. Uncertainty in collocated mobile measurements of air quality A. Whitehill et al. 10.1016/j.aeaoa.2020.100080
76. Study of the Characteristics and Comprehensive Fuzzy Assessment of Indoor Air Chemical Contamination in Public Buildings X. Liang et al. 10.3389/fpubh.2021.579299
77. A new mobile monitoring approach to characterize community-scale air pollution patterns and identify local high pollution zones Y. Chen et al. 10.1016/j.atmosenv.2022.118936
78. Application of a Common Methodology to Select in Situ CO2 Observations Representative of the Atmospheric Background to an Italian Collaborative Network P. Trisolino et al. 10.3390/atmos12020246
79. PLUME Dashboard: A free and open-source mobile air quality monitoring dashboard C. Kelly et al. 10.1016/j.envsoft.2022.105600
80. Identifying Patterns and Sources of Fine and Ultrafine Particulate Matter in London Using Mobile Measurements of Lung-Deposited Surface Area R. Shah et al. 10.1021/acs.est.2c08096
81. Characterizing Ultrafine Particle Mobile Monitoring Data for Epidemiology A. Doubleday et al. 10.1021/acs.est.3c00800
82. Identifying a regional aerosol baseline in the eastern North Atlantic using collocated measurements and a mathematical algorithm to mask high-submicron-number-concentration aerosol events F. Gallo et al. 10.5194/acp-20-7553-2020
83. Characterizing the spatial variability of local and background concentration signals for air pollution at the neighbourhood scale K. Shairsingh et al. 10.1016/j.atmosenv.2018.04.010
84. Variations in individuals’ exposure to black carbon particles during their daily activities: a screening study in Brazil A. Carvalho et al. 10.1007/s11356-018-2045-8
85. An integration modeling framework for individual-scale daily mobility estimation N. Luo et al. 10.1016/j.tbs.2023.100650
86. Parsimonious Random-Forest-Based Land-Use Regression Model Using Particulate Matter Sensors in Berlin, Germany J. Venkatraman Jagatha et al. 10.3390/s24134193
87. Design of an Air Pollution Monitoring Campaign in Beijing for Application to Cohort Health Studies S. Vedal et al. 10.3390/ijerph14121580
88. Identification of spikes associated with local sources in continuous time series of atmospheric CO, CO<sub>2</sub> and CH<sub>4</sub> A. El Yazidi et al. 10.5194/amt-11-1599-2018
89. Cyclists' exposure to air pollution under different traffic management strategies P. Krecl et al. 10.1016/j.scitotenv.2020.138043
90. Application of plume analysis to build land use regression models from mobile sampling to improve model transferability Y. Tan et al. 10.1016/j.atmosenv.2016.03.032
91. Methodology for high-quality mobile measurement with focus on black carbon and particle mass concentrations H. Alas et al. 10.5194/amt-12-4697-2019
92. High-spatial-resolution mapping and source apportionment of aerosol composition in Oakland, California, using mobile aerosol mass spectrometry R. Shah et al. 10.5194/acp-18-16325-2018
93. Preface P. Solomon & S. Dhaniyala 10.1080/02786826.2020.1706973
94. Ambient air quality measurements from a continuously moving mobile platform: Estimation of area-wide, fuel-based, mobile source emission factors using absolute principal component scores T. Larson et al. 10.1016/j.atmosenv.2016.12.037
95. Characteristics of PM2.5 Chemical Species in 23 Chinese Cities Identified Using a Vehicular Platform H. Chen et al. 10.3390/su16062340
96. Investigation of vehicle cold start primary NO2 emissions inferred from ambient monitoring data in the UK and their implications for urban air quality V. Matthaios et al. 10.1016/j.atmosenv.2018.11.031
97. Effectiveness evaluation of water-sprinkling in controlling urban fugitive road dust based on TRAKER method: A case study in Baoding, China Y. Zhang et al. 10.1016/j.jes.2021.12.005
98. Towards hyperlocal source identification of pollutants in cities by combining mobile measurements with atmospheric modeling J. Lin et al. 10.1016/j.atmosenv.2023.119995
99. Exploratory study of atmospheric methane enhancements derived from natural gas use in the Houston urban area N. Sanchez et al. 10.1016/j.atmosenv.2018.01.001
100. Air quality monitoring using mobile low-cost sensors mounted on trash-trucks: Methods development and lessons learned P. deSouza et al. 10.1016/j.scs.2020.102239