The reward and penalty for ozone pollution control caused by natural sources and regional transport: A case study in Guangdong province.

Ground-level O3 pollution in the Pearl River Delta region (PRD) is closely related to anthropogenic, natural emissions and regional transport. However, the interactions among different sources and natural intervention in modulating anthropogenic management have not been comprehensively assessed. Here, the WRF-CMAQ-MEGAN modeling system was utilized to simulate an O3 episode over PRD. The integrated source apportionment method (ISAM) and brute-force top-down combined with factor separation approach (BF-TD-FSA) were applied to quantify source contributions, impacts of individual or multiple sources on O3, and decouple interactions among various emissions; additionally, based on ISAM, O3 isopleths visualized MDA8 O3 response of different source types to anthropogenic perturbations. ISAM concluded considerable MDA8 O3 contributions of regional transport in PRD/NPRD (non-PRD areas in Guangdong province) (38.8 %/35.7 %), followed by anthropogenic (32.7 %/24.8 %), BVOC (biogenic volatile organic compounds, 23.8 %/20.3 %) and SNO (soil NO, ∼4 %) emissions. Compared to concentrated anthropogenic contributions, widespread natural contributions were observed across their source areas and along the transport pathways. The BF-TD also revealed that regional transport had the largest impact (>90 µg m-3) on MDA8 O3 while anthropogenic and BVOC emissions greatly affected downwind PRD (64.5 and 7.7 µg m-3). Negative synergy between anthropogenic and natural emissions (especially BVOC emission) suggested potential natural-induced intensification of anthropogenic impact during O3 management. The MDA8 O3 isopleths further demonstrated significant BVOC-induced reward and regional transport-induced penalty for anthropogenic NOx (ANOx) emission control benefits, leading to additional maximum MDA8 O3 decrease and increase by -27.5 and 13.8 µg m-3 in polluted high-emission grids. The natural-induced reward effect could impose loose requirements on anthropogenic reduction (decreased by 13.3 %-17.7 %) if there were no regional transport-induced control penalty. It is advisable to prioritize ANOx control and seek collaboration on air quality management with neighboring provinces to maximize the natural-induced control reward and achieve desired targets with minimal human efforts.

Examining trends and variability of PM2.5-associated organic and elemental carbon in the megacity of Beijing, China: Insight from decadal continuous in-situ hourly observations.

Organic carbon (OC) and elemental carbon (EC) in fine particulate matter (PM2.5) play pivotal roles in impacting human health, air quality, and climate change dynamics. Long-term monitoring datasets of OC and EC in PM2.5 are indispensable for comprehending their temporal variations, spatial distribution, evolutionary patterns, and trends, as well as for assessing the effectiveness of clean air action plans. This study presents and scrutinizes a comprehensive 10-year hourly dataset of PM2.5-bound OC and EC in the megacity of Beijing, China, spanning from 2013 to 2022. Throughout the entire study period, the average concentrations of OC and EC were recorded at 8.8 ± 8.7 and 2.5 ± 3.0 µg/m3, respectively. Employing the seasonal and trend decomposition methodology, specifically the locally estimated scatter plot smoothing method combined with generalized least squares with the autoregressive moving average method, the study observed a significant decline in OC and EC concentrations, reducing by 5.8 % yr-1 and 9.9 % yr-1 at rates of 0.8 and 0.4 µg/m3 yr-1, respectively. These declining trends were consistently verified using Theil-Sen method. Notably, the winter months exhibited the most substantial declining trends, with rates of 9.3 % yr-1 for OC and 10.9 % yr-1 for EC, aligning with the positive impact of the implemented clean air action plan. Weekend spikes in OC and EC levels were attributed to factors such as traffic regulations and residential emissions. Diurnal variations showcased higher concentrations during nighttime and lower levels during daytime. Although meteorological factors demonstrated an overall positive impact with average reduction in OC and EC concentrations by 8.3 % and 8.7 %, clean air action plans including the Air Pollution Prevention and Control Action Plan (2013-2017) and the Three-Year Action Plan to Win the Blue Sky War (2018-2020) have more contributions in reducing the OC and EC concentrations with mass drop rates of 87.1 % and 89.2 % and 76.7 % and 96.7 %, respectively. Utilizing the non-parametric wind regression method, significant concentration hotspots were identified at wind speeds of ≤2 m/s, with diffuse signals recorded in the southwestern wind sectors at wind speeds of approximately 4-5 m/s. Interannual disparities in potential source regions of OC and EC were evident, with high potential source areas observed in the southern and northwestern provinces of Beijing from 2013 to 2018. In contrast, during 2019-2022, potential source areas with relatively high values of potential source contribution function were predominantly situated in the southern regions of Beijing. This analysis, grounded in observational data, provides insights into the decadal changes in the major atmospheric composition of PM2.5 and facilitates the evaluation of the efficacy of control policies, particularly relevant for developing countries.

Explainable ensemble machine learning revealing the effect of meteorology and sources on ozone formation in megacity Hangzhou, China.

Megacity Hangzhou, located in eastern China, has experienced severe O3 pollution in recent years, thereby clarifying the key drivers of the formation is essential to suppress O3 deterioration. In this study, the ensemble machine learning model (EML) coupled with Shapley additive explanations (SHAP), and positive matrix factorization were used to explore the impact of various factors (including meteorology, chemical components, sources) on O3 formation during the whole period, pollution days, and typical persistent pollution events from April to October in 2021-2022. The EML model achieved better performance than the single model, with R2 values of 0.91. SHAP analysis revealed that meteorological conditions had the greatest effects on O3 variability with the contribution of 57 %-60 % for different pollution levels, and the main drivers were relative humidity and radiation. The effects of chemical factors on O3 formation presented a positive response to volatile organic compounds (VOCs) and fine particulate matter (PM2.5), and a negative response to nitrogen oxides (NOx). Oxygenated compounds (OVOCs), alkenes, and aromatic of VOCs subgroups had higher contribution; additionally, the effects of PM2.5 and NOx were also important and increased with the O3 deterioration. The impact of seven emission sources on O3 formation in Hangzhou indicated that vehicle exhaust (35 %), biomass combustion (16 %), and biogenic emissions (12 %) were the dominant drivers. However, for the O3 pollution days, the effects of biomass combustion and biogenic emissions increased. Especially in persistent pollution events with highest O3 concentrations, the magnitude of biogenic emission effect elevated significantly by 156 % compared to the whole situations. Our finding revealed that the combination of the EML model and SHAP analysis could provide a reliable method for rapid diagnosis of the cause of O3 pollution at different event scales, supporting the formulation of control measures.

Comparative analysis for the impacts of VOC subgroups and atmospheric oxidation capacity on O3 based on different observation-based methods at a suburban site in the North China Plain.

The persistent O3 pollution in the Beijing-Tianjin-Hebei (BTH) region remains unresolved, largely due to limited comprehension of O3-precursor relationship and photochemistry drivers. In this work, intraday O3 sensitivity evolution from VOC-limited (volatile organic compound) regime in the forenoon to transition regime in the late afternoon was inferred by relative incremental reactivity (RIR) in summer 2019 at Xianghe, a suburban site in BTH region, suggesting that VOC-focused control policy could combine with stringent afternoon NOx control. Then detailed impacts of VOC subgroups on O3 formation were further comprehensively quantified by parametric OH reactivity (KOH), O3 formation potential (OFP), as well as RIR weighted value and O3 formation path tracing (OFPT) approach based on photochemical box model. O3 episode days corresponded to stronger O3 formation, depicted by higher KOH (10.4 s-1), OFP (331.7 µg m-3), RIR weighted value (1.2), and F(O3)-OFPT (15.5 ppbv h-1). High proportions of isoprene and OVOCs (oxygenated VOCs) to the total KOH and the OFPT method were demonstrated whereas results of OFP and RIR-weighted presented extra great impacts of aromatics on O3 formation. The OFPT approach captured the process that has already happened and included final O3 response to the original VOC, thus reliable for replicating VOC impacts. The comparison results of the four methods showed similarities when utilizing KOH and OFPT methods, which reveals that the potential applicability of simple KOH for contingency VOC control and more complex OFPT method for detailed VOC- and source-oriented control during policy-making. To investigate propulsion of VOC-involved O3 photochemistry, atmospheric oxidation capacity (AOC) was quantified by two atmospheric oxidation indexes (AOI). Both AOIp_G (7.0 × 107 molec cm-3 s-1, potential AOC calculated by oxidation reaction rates) and AOIe_G (8.5 µmol m-3, estimated AOC given redox electron transfer for oxidation products) were stronger on O3 episode days, indicating that AOC promoted the radical cycling initiated from VOC oxidation and subsequent O3 production. Result-oriented AOIe_G reasonably characterized actual AOC inferred by good linear correlation between AOIe_G and O3 concentrations compared to process-oriented AOIp_G. Therefore, with continuous NOx abatement, AOIe_G should be considered to represent actual AOC, also O3-inducing ability.