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https://doi.org/10.2139/ssrn.4757120

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/essoar.10507721.1openalex-extracted
inferredcites →https://doi.org/10.1016/j.aosl.2022.100189openalex-extracted
Impacts of ENSO on wintertime PM2.5 pollution over China during 2014–2021
inferredcites →https://doi.org/10.1016/j.apr.2018.01.012openalex-extracted
Effects of land use and landscape pattern on PM2.5 in Yangtze River Delta, China
inferredcites →https://doi.org/10.1016/j.apr.2021.101151openalex-extracted
Analysis of spatiotemporal variation of PM2.5 and its relationship to land use in China
inferredcites →https://doi.org/10.1016/j.atmosenv.2021.118273openalex-extracted
Validation and comparison of high-resolution MAIAC aerosol products over Central Asia
inferredcites →https://doi.org/10.1016/j.atmosenv.2022.119520openalex-extracted
Correlation between surface PM2.5 and O3 in eastern China during 2015–2019: Spatiotemporal variations and meteorological impacts
inferredcites →https://doi.org/10.1016/j.chemosphere.2015.12.118openalex-extracted
Spatial-temporal characteristics and determinants of PM2.5 in the Bohai Rim Urban Agglomeration
inferredcites →https://doi.org/10.1016/j.chemosphere.2020.129140openalex-extracted
A practical framework for predicting residential indoor PM2.5 concentration using land-use regression and machine learning methods
inferredcites →https://doi.org/10.1016/j.chemosphere.2021.129611openalex-extracted
Regression-based flexible models for photochemical air pollutants in the national capital territory of megacity Delhi
inferredcites →https://doi.org/10.1016/j.chemosphere.2021.133388openalex-extracted
Predictive modeling of groundwater nitrate pollution and evaluating its main impact factors using random forest
inferredcites →https://doi.org/10.1016/j.chemosphere.2022.133813openalex-extracted
Spatiotemporal characteristics of PM2.5 and ozone concentrations in Chinese urban clusters
inferredcites →https://doi.org/10.1016/j.ecoleng.2012.12.045openalex-extracted
Detecting land use-water quality relationships from the viewpoint of ecological restoration in an urban area
inferredcites →https://doi.org/10.1016/j.ecolind.2018.09.050openalex-extracted
Landscape pattern as an indicator of urban air pollution of particulate matter in Poland
inferredcites →https://doi.org/10.1016/j.ecolind.2022.108810openalex-extracted
Seasonal variations for combined effects of landscape metrics on land surface temperature (LST) and aerosol optical depth (AOD)
inferredcites →https://doi.org/10.1016/j.ecolind.2023.110409openalex-extracted
Estimating the nonlinear response of landscape patterns to ecological resilience using a random forest algorithm: Evidence from the Yangtze River Delta
inferredcites →https://doi.org/10.1016/j.ecolind.2023.110746openalex-extracted
Assessing the potential impacts of LULC change on urban air quality in Dhaka city
inferredcites →https://doi.org/10.1016/j.eiar.2022.106840openalex-extracted
Assessing drivers of coordinated control of ozone and fine particulate pollution: Evidence from Yangtze River Delta in China
inferredcites →https://doi.org/10.1016/j.envint.2019.05.075openalex-extracted
Comparison of health and economic impacts of PM2.5 and ozone pollution in China
inferredcites →https://doi.org/10.1016/j.envpol.2018.09.026openalex-extracted
Using MAIAC AOD to verify the PM2.5 spatial patterns of a land use regression model
inferredcites →https://doi.org/10.1016/j.envpol.2023.122189openalex-extracted
Spatio-temporal variations of PM2.5 and O3 in China during 2013–2021: Impact factor analysis
inferredcites →https://doi.org/10.1016/j.envres.2015.04.014openalex-extracted
A national fine spatial scale land-use regression model for ozone
inferredcites →https://doi.org/10.1016/j.jclepro.2015.05.005openalex-extracted
The influential factors of urban PM2.5 concentrations in China: a spatial econometric analysis
inferredcites →https://doi.org/10.1016/j.jclepro.2019.117744openalex-extracted
The relationships between urban landscape patterns and fine particulate pollution in China: A multiscale investigation using a geographically weighted regression model
inferredcites →https://doi.org/10.1016/j.jclepro.2019.118741openalex-extracted
Response of PM2.5 pollution to land use in China
inferredcites →https://doi.org/10.1016/j.jclepro.2023.136706openalex-extracted
The division of PM2.5-O3 composite airborne pollution across China based on spatiotemporal clustering
inferredcites →https://doi.org/10.1016/j.rse.2005.11.016openalex-extracted
Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes
inferredcites →https://doi.org/10.1016/j.rse.2020.112136openalex-extracted
Reconstructing 1-km-resolution high-quality PM2.5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications
inferredcites →https://doi.org/10.1016/j.rse.2021.112775openalex-extracted
Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China
inferredcites →https://doi.org/10.1016/j.scitotenv.2018.12.276openalex-extracted
Improved population mapping for China using remotely sensed and points-of-interest data within a random forests model
inferredcites →https://doi.org/10.1016/j.scitotenv.2019.01.227openalex-extracted
Responses of PM2.5 and O3 concentrations to changes of meteorology and emissions in China
inferredcites →https://doi.org/10.1016/j.scitotenv.2019.135602openalex-extracted
Effects of land-use patterns on PM2.5 in China's developed coastal region: Exploration and solutions
inferredcites →https://doi.org/10.1016/j.scitotenv.2020.138676openalex-extracted
Characteristics of aerosol optical depth over land types in central Asia
inferredcites →https://doi.org/10.1016/j.scitotenv.2022.155975openalex-extracted
Regional demarcation of synergistic control for PM2.5 and ozone pollution in China based on long-term and massive data mining
inferredcites →https://doi.org/10.1016/j.scs.2022.103722openalex-extracted
The dominant factors and influence of urban characteristics on land surface temperature using random forest algorithm
inferredcites →https://doi.org/10.1016/j.scs.2022.103841openalex-extracted
Analysis of the spatial characteristics of inhalable particulate matter concentrations under the influence of a three-dimensional landscape pattern in Xi'an, China
inferredcites →https://doi.org/10.1016/j.scs.2024.105296openalex-extracted
Assessing climate/air quality synergies and cost-effectiveness for Beijing transportation: Insights into sustainable development
inferredcites →https://doi.org/10.1016/j.scs.2024.105309openalex-extracted
Combined effects of urban forests on land surface temperature and PM2.5 pollution in the winter and summer
inferredcites →https://doi.org/10.1016/s0140-6736(20)30752-2openalex-extracted
Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
inferredcites →https://doi.org/10.1016/s1352-2310(02)00188-7openalex-extracted
Spectral analysis of weekday–weekend differences in ambient ozone, nitrogen oxide, and non-methane hydrocarbon time series in California
inferredcites →https://doi.org/10.1021/acs.est.0c04910openalex-extracted
The Role of Temperature and NOx in Ozone Trends in the Los Angeles Basin
inferredcites →https://doi.org/10.1029/2022ef002936openalex-extracted
Marked Impacts of Pollution Mitigation on Crop Yields in China
inferredcites →https://doi.org/10.1038/nature13774openalex-extracted
High secondary aerosol contribution to particulate pollution during haze events in China
inferredcites →https://doi.org/10.1038/s41467-020-15319-4openalex-extracted
Stronger policy required to substantially reduce deaths from PM2.5 pollution in China
inferredcites →https://doi.org/10.1093/nsr/nwaa137openalex-extracted
Enhanced secondary pollution offset reduction of primary emissions during COVID-19 lockdown in China
inferredcites →https://doi.org/10.1126/sciadv.abc1176openalex-extracted
Ozone affects plant, insect, and soil microbial communities: A threat to terrestrial ecosystems and biodiversity
inferredcites →https://doi.org/10.1126/science.277.5322.116openalex-extracted
Chemical Coupling Between Atmospheric Ozone and Particulate Matter
inferredcites →https://doi.org/10.13227/j.hjkx.202002096openalex-extracted
[Aerosol Optical Properties over the Ebinur Region].
inferredcites →https://doi.org/10.13227/j.hjkx.202009083openalex-extracted
[Temporal and Spatial Distribution Characteristics of Aerosol Optical Properties in Urban Agglomerations on the North Slope of the Tianshan Mountains].
inferredcites →https://doi.org/10.14358/pers.85.2.145openalex-extracted
Ground-Level Ozone Concentration and Landscape Patterns in China's Urban Areas
inferredcites →https://doi.org/10.31223/osf.io/hvuzyopenalex-extracted
inferredcites →https://doi.org/10.3390/atmos8030059openalex-extracted
Inverse Relations of PM2.5 and O3 in Air Compound Pollution between Cold and Hot Seasons over an Urban Area of East China
inferredcites →https://doi.org/10.3390/en12132545openalex-extracted
Correlation Analysis between Land Use/Cover Change and Air Pollutants—A Case Study in Wuyishan City
inferredcites →https://doi.org/10.3390/rs9090918openalex-extracted
Scale- and Region-Dependence in Landscape-PM2.5 Correlation: Implications for Urban Planning
inferredcites →https://doi.org/10.3390/su8070677openalex-extracted
Effect of Land Use and Cover Change on Air Quality in Urban Sprawl
inferredcites →https://doi.org/10.5194/acp-15-2969-2015openalex-extracted
Exploring the severe winter haze in Beijing: the impact of synoptic weather, regional transport and heterogeneous reactions
inferredcites →https://doi.org/10.5194/acp-16-7411-2016openalex-extracted
Real-time measurements of secondary organic aerosol formation and aging from ambient air in an oxidation flow reactor in the Los Angeles area
inferredcites →https://doi.org/10.5194/acp-20-13455-2020openalex-extracted
Sensitivity analysis of the surface ozone and fine particulate matter to meteorological parameters in China
inferredcites →https://doi.org/10.5194/acp-20-3273-2020openalex-extracted
Improved 1 km resolution PM 2.5 estimates across China using enhanced space–time extremely randomized trees

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1016/j.geosus.2025.100352openalex-snapshot
Navigating the safe and just operating space for urban systems: A cross-scale landscape approach
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