2024
Characterization of winter PM2.5 source contributions and impacts of meteorological conditions and anthropogenic emission changes in the Sichuan Basin, 2002–2020
Yaohan Xian, Yang Zhang#, Zhihong Liu, Haofan Wang, Tianxin Xiong (# corresponding author)
Science of The Total Environment (STE) 2024
In this study, the Weather Research and Forecasting (WRF) model and Community Multiscale Air Quality–Integrated Source Apportionment Method (CMAQ–ISAM) were utilized, which were integrated with the Multiresolution Emission Inventory for China (MEIC) emission inventory, to simulate winter PM2.5 concentrations, regional transport, and changes in emission source contributions in the Sichuan basin (SCB) from 2002 to 2020, considering variations in meteorological conditions and anthropogenic emissions. The results indicated a gradual decrease in the basin's winter average PM2.5 concentration from 300 μg/m3 to 120 μg/m3, with the most significant decrease occurring after 2014, reflecting the actual impact of China's air pollution control measures. Spatially, the main pollution area shifted from Chongqing to Chengdu and the western basin. The sources of PM2.5 at the eastern and western margins of the basin have remained stable and have been dominated by local emissions for many years, while the sources of PM2.5 in the central part of the basin have evolved from a multiregional co-influenced source during the early period to a high proportion of local emissions; except for boundary condition sources, residential sources were the main PM2.5 sources in the basin (approximately 29.70 %), followed by industrial sources (approximately 14.11 %). Industrial sources exhibited higher contributions in Chengdu and Chongqing and gradually stabilized with residential sources over the years, while residential sources dominated in the eastern and western parts of the basin and exhibited a declining trend. Meteorological conditions exacerbated pollution in the whole basin from 2008 to 2014, especially in the west (21–40 μg/m3). The eastern basin and Chongqing exhibited more years with alleviated meteorological pollution, including a 40+ μg/m3 decrease in Chongqing from 2002 to 2005. Reduced anthropogenic emissions alleviated annual pollution levels, with a greater reduction (> −20 μg/m3) after 2011 due to pollution control measures.
MEIAT-CMAQ: A modular emission inventory allocation tool for Community Multiscale Air Quality Model
Haofan Wang, Jiaxin Qiu, Yiming Liu#, Qi Fan, Xiao Lu, Yang Zhang, Kai Wu, Ao Shen, Yifei Xu, Yinbao Jin, Yuqi Zhu, Jiayin Sun, Haolin Wang (# corresponding author)
Atmospheric Environment (AE) 2024 Spotlight
The Modular Emission Inventory Allocation Tool for Community Multiscale Air Quality Model (MEIAT-CMAQ) refines emission inventories by providing detailed spatial (horizontal and vertical), temporal, and species allocations, enhancing the accuracy of CMAQ performance. Its efficient algorithm and modular design offer flexibility for managing both gridded and tabulated inventories, widely used in various sectors. In addition, the shapefiles with specific shapes supported by MEIAT-CMAQ can address the allocation challenges in transportation emissions. The evaluation of MEIAT-CMAQ, using model-ready inventories before (BASE scenario), and after allocation without (EXPR scenario) or with (EXPR-V scenario) vertical allocation, demonstrates significant improvements in the mean bias (MB) of gaseous pollutants (O3, NO2, CO). In both the EXPR and EXPR-V scenarios, the MB for O3 exhibits notable enhancements, with respective improvements of 5.7% and 26.9%. For NO2, corresponding MB improvements are even more pronounced, reaching 27.6% and 61.7% in the EXPR and EXPR-V scenarios, respectively. Likewise, enhancements are observed in the MBs of CO, demonstrating increases of 8.4% and 45.2% in the EXPR and EXPR-V scenarios, respectively. Moreover, with regard to spatial accuracy, the incorporation of the MEIAT-CMAQ model yields significant improvements. Specifically, in the EXPR scenarios, spatial accuracy for O3 and NO2 demonstrates respective enhancements of 13.5% and 9.5%. Furthermore, the inclusion of vertical allocation leads to additional enhancements in CO, NO2, and PM2.5, resulting in improvements of 17.6%, 16.6%, and 23.2%, respectively. MEIAT-CMAQ provides an efficient method for transforming coarse-resolution emission inventories into high-resolution files directly useable in the model, offering enhanced flexibility for users to select any period for generating model-ready emission files. This capability provides substantial technical support for automating processes within business departments and significantly improves the performance of high-resolution modeling and forecasting.
Source apportionment and formation of warm season ozone pollution in Chengdu based on CMAQ-ISAM
Yaohan Xian, Yang Zhang#, Zhihong Liu, Haofan Wang, Junjie Wang, Chao Tang (# corresponding author)
Urban Climate 2024
In this study, the WRF-CMAQ model integrated with BEM urban canopy model was used to simulate the concentrations of Ozone ( O3 ) and its precursors, NOx, and VOCs, in warm season of Chengdu, conduct source apportionment and formation analysis. The results show that the O3 in Chengdu exhibits a west-high/east-low spatial pattern, attributable to nearly 40% contribution from boundary sources representing the transport role of the Sichuan Basin, regional sources from districts emitting high precursor concentrations, and increasing biogenic contributions from western areas due to rising BVOCs emissions during the warm season. NOx from traffic and VOCs from industrial sources, both prevalent in Chengdu's high urban density areas, chemically react to form O3, making these sectors primary contributors to O3. NOx photochemical reactions producing O3 occur at 150 m–2500 m with peak generation rates of 10 μg/(m3·hr). Ground-level NO titration removal is most significant during heavy traffic (14:00–21:00), ranging from −70 to −200 μg/(m3·hr). O3 is replenished through similar rates of daytime vertical diffusion and nighttime horizontal advection, correlating with urban density across regions. Controlling Chengdu's warm season O3 requires focusing on long-distance external transport and regional precursor emission reductions, with strategies tailored to local urban characteristics.
Measurement report: Assessing the impacts of emission uncertainty on aerosol optical properties and radiative forcing from biomass burning in peninsular Southeast Asia
Yinbao Jin, Yiming Liu#, Xiao Lu, Xiaoyang Chen, Ao Shen, Haofan Wang, Yinping Cui, Yifei Xu, Siting Li, Jian Liu, Ming Zhang, Yingying Ma, Qi Fan# (# corresponding author)
Atmospheric Chemistry and Physics 2024
Despite significant advancements in improving the dataset for biomass burning (BB) emissions over the past few decades, uncertainties persist in BB aerosol emissions, impeding the accurate assessment of simulated aerosol optical properties (AOPs) and direct radiative forcing (DRF) during wildfire events in global and regional models. This study assessed AOPs (including aerosol optical depth (AOD), aerosol absorption optical depth (AAOD), and aerosol extinction coefficients (AECs)) and DRF using eight independent BB emission inventories applied to the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) during the BB period (March 2019) in peninsular Southeast Asia (PSEA), where the eight BB emission inventories were the Global Fire Emissions Database version 4.1s (GFED), Fire INventory from NCAR version 1.5 (FINN1.5), the Fire Inventory from NCAR version 2.5 MOS (MODIS fire detections; FINN2.5 MOS), the Fire Inventory from NCAR version 2.5 MOSVIS (MODIS + VIIRS fire detections; FINN2.5 MOSVIS), Global Fire Assimilation System version 1.2s (GFAS), Fire Energetics and Emissions Research version 1.0 (FEER), Quick Fire Emissions Dataset version 2.5 release 1 (QFED), and Integrated Monitoring and Modelling System for Wildland FIRES project version 2.0 (IS4FIRES), respectively. The results show that in the PSEA region, organic carbon (OC) emissions in the eight BB emission inventories differ by a factor of about 9 (0.295–2.533 Tg M−1), with 1.09 ± 0.83 Tg M−1 and a coefficient of variation (CV) of 76 %. High-concentration OC emissions occurred primarily in savanna and agricultural fires. The OC emissions from the GFED and GFAS are significantly lower than the other inventories. The OC emissions in FINN2.5 MOSVIS are approximately twice as high as those in FINN1.5. Sensitivity analysis of AOD simulated by WRF-Chem to different BB emission datasets indicated that the FINN scenarios (v1.5 and 2.5) significantly overestimate AOD compared to observation (VIIRS), while the other inventories underestimate AOD in the high-AOD (HAOD; AOD > 1) regions range from 15–22.5∘ N, 97–110∘ E. Among the eight schemes, IS4FIRES and FINN1.5 performed better in terms of AOD simulation consistency and bias in the HAOD region when compared to AERONET sites. The AAOD in WRF-Chem during the PSEA wildfire period was assessed, using satellite observations (TROPOMI) and AERONET data, and it was found that the AAOD simulated with different BB schemes did not perform as well as the AOD. The significant overestimation of AAOD by FINN (v1.5 and 2.5), FEER, and IS4FIRES schemes in the HAOD region, with the largest overestimation for FINN2.5 MOSVIS. FINN1.5 schemes performed better in representing AAOD at AERONET sites within the HAOD region. The simulated AOD and AAOD from FINN2.5 MOSVIS always show the best correlation with the observations. AECs simulated by WRF-Chem with all the eight BB schemes trends were consistent with CALIPSO in the vertical direction (0.5 to 4 km), demonstrating the efficacy of the smoke plume rise model used in WRF-Chem to simulate smoke plume heights. However, the FINN (v1.5 and 2.5) schemes overestimated AECs, while the other schemes underestimated it. In the HAOD region, BB aerosols exhibited a daytime shortwave radiative forcing of −32.60 ± 24.50 W m−2 at the surface, positive forcing (1.70 ± 1.40 W m−2) in the atmosphere, and negative forcing (−30.89 ± 23.6 W m−2) at the top of the atmosphere. Based on the analysis, FINN1.5 and IS4FIRES are recommended for accurately assessing the impact of BB on air quality and climate in the PSEA region.
2023
Nighttime ozone in the lower boundary layer: insights from 3-year tower-based measurements in South China and regional air quality modeling
Guowen He, Cheng He, Haofan Wang, Xiao Lu#, Chenglei Pei, Xiaonuan Qiu, Chenxi Liu, Yiming Wang, Nanxi Liu, Jinpu Zhang, Lei Lei, Yiming Liu, Haichao Wang, Tao Deng, Qi Fan, Shaojia Fan (# corresponding author)
Atmospheric Chemistry and Physics (ACP) 2023 Spotlight
Nighttime ozone in the lower boundary layer regulates atmospheric chemistry and surface ozone air quality, but our understanding of its vertical structure and impact is largely limited by the extreme sparsity of direct measurements. Here we present 3-year (2017–2019) measurements of ozone in the lower boundary layer (up to 500 m) from the Canton Tower in Guangzhou, the core megacity in South China, and interpret the measurements with a 1-month high-resolution chemical simulation from the Community Multiscale Air Quality (CMAQ) model. Measurements are available at 10, 118, 168, and 488 m, with the highest (488 m) measurement platform higher than the typical height of the nighttime stable boundary layer that allows direct measurements of ozone in the nighttime residual layer (RL). We find that ozone increases with altitude in the lower boundary layer throughout the day, with a vertical ozone gradient between the 10 and 488 m heights (ΔOH10–488 m) of 3.6–6.4 ppbv hm−1 in nighttime and 4.4–5.8 ppbv hm−1 in daytime. We identify a high ozone residual ratio, defined as the ratio of ozone concentration averaged over nighttime to that in the afternoon (14:00–17:00 LT), of 69 %–90 % in January, April, and October, remarkably higher than that in the other three layers (29 %–51 %). Ozone in the afternoon convective mixing layer provides the source of ozone in the RL, and strong temperature inversion facilitates the ability of RL to store ozone from the daytime convective mixing layer. The tower-based measurement also indicates that the nighttime surface Ox (Ox= O3+NO2) level can be an effective indicator of RL ozone if direct measurement is not available. We further find significant influences of nocturnal RL ozone on both the nighttime and the following day's daytime surface ozone air quality. During the surface nighttime ozone enhancement (NOE) event, we observe a significant decrease in ozone and an increase in NO2 and CO at the 488 m height, in contrast to their changes at the surface, a typical feature of enhanced vertical mixing. The enhanced vertical mixing leads to an NOE event by introducing ozone-rich and NOx-poor air into the RL to enter the nighttime stable boundary layer. The CMAQ model simulations also demonstrate an enhanced positive contribution of vertical diffusion (ΔVDIF) to ozone at the 10 and 118 m heights and a negative contribution at the 168 and 488 m heights during the NOE event. We also observe a strong correlation between nighttime RL ozone and the following day's surface maximum daily 8 h average (MDA8) ozone. This is tied to enhanced vertical mixing with the collapse of nighttime RL and the development of a convective mixing layer, which is supported by the CMAQ diagnosis of the ozone budget, suggesting that the mixing of ozone-rich air from nighttime RL downward to the surface via the entrainment is an important mechanism for aggravating ozone pollution the following day. We find that the bias in CMAQ-simulated surface MDA8 ozone the following day shows a strong correlation coefficient (r= 0.74) with the bias in nighttime ozone in the RL, highlighting the necessity to correct air quality model bias in the nighttime RL ozone for accurate prediction of daytime ozone. Our study thus highlights the value of long-term tower-based measurements for understanding the coupling between nighttime ozone in the RL, surface ozone air quality, and boundary layer dynamics.
Assessment of tropospheric ozone simulations in a regional chemical transport model using GEOS-Chem outputs as chemical boundary conditions
Yuqi Zhu, Yiming Liu#, Siting Li, Haolin Wang, Xiao Lu, Haichao Wang, Chong Shen, Xiaoyang Chen, Pakwai Chan, Ao Shen, Haofan Wang, Yinbao Jin, Yifei Xu, Shaojia Fan, Qi Fan# (# corresponding author)
Science of The Total Environment (STE) 2023
Regional chemical transport models (e.g., Community Multiscale Air Quality (CMAQ) Modeling System) are widely used to simulate the physical and chemical process of regional ozone (O3) pollution and its variation trend in recent years. However, chemical boundary condition (CBC) is an important input of these models and contributes to the model bias against observations. In this study, we develop a tool named GC2CMAQ that provides the CMAQ model with the CBCs from the GEOS-Chem simulation. Two experiments using different CBCs were conducted to evaluate their effect on seasonal O3 simulation in China. The Default experiment utilized the model-default static condition (the relatively clean atmosphere in the eastern United States), and the GC experiment employed the GEOS-Chem simulation results. Compared with the observation, the GC experiment has a much better performance in reproducing elevated O3 levels in the higher troposphere and lower stratosphere during different seasons. Near the earth's surface, the simulated concentrations of pollutants O3 (and PM2.5) in the GC experiment were also closer to the observation in April and July. The accuracy of simulation results in provinces close to the boundary was improved by approximately 20 %–30 % relative to the Default experiment. The CBCs provided by GEOS-Chem enabled a better simulation of stratosphere-troposphere O3 exchange in late spring and early summer, which then affected the pollutant concentration near surfaces through vertical transport. This finding was confirmed by a case study in southwestern Tibet on April 28, 2017, in which we quantified the contributions of different physical and chemical processes to O3 variations at different altitudes using the process analysis method. This study highlights the importance of using a reliable CBC for the regional chemical transport model to derive a better performance of O3 simulation.
2022
Impact of Urbanization on Meteorology and Air Quality in Chengdu, a Basin City of Southwestern China
Haofan Wang, Zhihong Liu, Kai Wu, Jiaxin Qiu, Yang Zhang#, Bangping Ye, Min He (# corresponding author)
Frontiers in Ecology and Evolution (FEE) 2022
Rapid urbanization has the potential to fundamentally perturb energy budget and alter urban air quality. While it is clear that urban meteorological parameters are sensitive to urbanization-induced changes in landscapes, a gap exists in our knowledge about how changes in land use and land cover affect the dynamics of urban air quality. Herein, we simulated a severe O3 episode (10–16 July 2017) and a highly polluted PM2.5 episode (25–30 December 2017) and assessed the changes of meteorological phenomenon and evolution of air pollutants induced by urbanization. We found that the urban expansion area (i.e., land use transition from natural to urban surfaces between 2000 and 2017, UEA) has a significant increase in nocturnal 2-m temperature (T2) with maximum values reaching 3 and 4°C in summer and winter, respectively. In contrast, UEA experienced cooling in the daytime with stronger reductions of T2 in winter than in summer. The T2 variability is primarily attributed to the intense thermal inertia and high heat capacity of the urban canopy and the shadowing effect caused by urbanization. Owing to increased surface roughness and decreased surface albedo as well as shadowing effects, the ventilation index (VI) of UEA increased up to 1,200 m2/s in winter while decreased up to 950 m2/s in summer. Changes in meteorological phenomenon alter physical and chemical processes associated with variations in PM2.5 and O3 concentrations. Urbanization leads to enhanced vertical advection process and weakened aerosol production, subsequently causing PM2.5 levels to decrease by 33.2 μg/m3 during the day and 4.6 μg/m3 at night, respectively. Meanwhile, O3 levels increased by 61.4 μg/m3 at 20:00 due to the reduction of horizontal advection induced by urbanization, while O3 concentrations changed insignificantly at other times. This work provides valuable insights into the effects of urbanization on urban meteorology and air quality over typical megacities, which support informed decision-making for urban heat and air pollution mitigation.
2021
Impact of different urban canopy models on air quality simulation in Chengdu, southwestern China
Haofan Wang, Zhihong Liu, Yang Zhang#, Zhengyang Yu, Chunrong Chen (# corresponding author)
Atmospheric Environment (AE) 2021
Urban air pollution has emerged as a prominent public health concern in megacities and highly developed city clusters. Accurate modeling of urban air quality over complex terrain is challenging due to heterogeneous urban landscapes and multiscale land-atmosphere interactions. In this study, we investigated the applicability of urban canopy models in the Weather Research and Forecast (WRF) model and assessed the impacts of implementing these models on the urban air quality simulation in the Community Multiscale Air Quality (CMAQ) model over the megacity Chengdu, southwestern China. The land use and land cover of Chengdu were updated in WRF by using the land-use products in 2017 from the Moderate-resolution Imaging Spectroradiometer (MODIS). Sensitivity experiments with various urban canopy models were conducted to investigate the feasibility of different urban canopy models on WRF-CMAQ simulations. We found that the SLAB model significantly underestimates NO2 and PM2.5 concentrations, with mean fractional bias in winter (summer) reaching 52.93% (−50.34%) and −102.82% (−23.12%), respectively. Such large biases are mainly attributed to overpredicted wind speeds resulting from the flat structure in the SLAB model. In contrast, the BEM (a multilayer urban canopy model coupled with air-conditioning systems) model yields the best model performance in both winter and summer, with mean fractional errors of 33.15% (38.96%) and 34.10% (33.15%) for NO2 and PM2.5 in winter (summer), respectively. The UCM (a single-layer urban canopy model) model illustrates good performance in summer, with MFBs of 25.61% for NO2 and 19.03% for PM2.5 , while NO2 and PM2.5 concentrations are overestimated in winter, with MFBs of 62.58% and 38.19%, respectively. In contrast, BEP (a multilevel urban canopy model)-modelled NO2 (MFB: 37.18%) and PM2.5 (MFB: 18.72%) correlate well with observations in winter, while significantly overestimated air pollutant concentrations in summer with MFBs of NO2 and PM2.5 of 49.70% and 44.50%, respectively. In general, the BEP model and the BEM model are well suited for air quality simulations over Chengdu in winter, and the BEM model could be considered for air quality simulations in summer. Furthermore, we assessed the effects of extensive usage of air conditioning systems in Chengdu during summertime, and the results suggest that using air conditioning systems facilitates the dispersion of air pollutants over Chengdu. This study pinpoints the limitations of default WRF configurations and tests the applicability of urban canopy models in the WRF-CMAQ model over Chengdu, in addition highlighting the crucial role of urban canopy models in urban meteorological-air quality simulations.