Seasonal Production Research Articles

Skillful seasonal prediction of wind energy resources in the contiguous United States

A key challenge with the wind energy utilization is that winds, and thus wind power, are highly variable on seasonal to interannual timescales because of atmospheric variability. There is a growing need of skillful seasonal wind energy prediction for energy system planning and operation. Here we demonstrate model’s capability in producing skillful seasonal wind energy prediction over the U.S. Great Plains during peak energy seasons (winter and spring), using seasonal prediction products from a climate model. The dominant source of that skillful prediction mainly comes from year-to-year variations of El Niño-Southern Oscillation in the tropical Pacific, which alters large-scale wind and storm track patterns over the United States. In the Southern Great Plains, the model can predict strong year-to-year wind energy changes with high skill multiple months in advance. Thus, this seasonal wind energy prediction capability offers potential benefits for optimizing wind energy utilization during peak energy production seasons.

Energy Balance and Greenhouse Gas (GHG) Emissions of Sesame (Sesamum indicum L.) Production in Türkiye

The objective of this study was to determine the energy use and greenhouse gas emissions associated with sesame production. Energy use efficiency indicators and greenhouse gas emission rates were calculated for the 2022-2023 production season. The energy input and output for sesame production were found to be 12079.15 MJ ha-1 and 30052.44 MJ ha-1, respectively. The study found an energy use efficiency of 2.49, with a specific energy of 12.20 MJ kg-1, an energy productivity of 0.08 kg MJ-1, and a net energy value of 17973.29 MJ ha-1. The direct and indirect energy inputs were calculated to be 4584.41 MJ ha-1 (37.95%) and 7494.74 MJ ha-1 (62.05%), while the renewable and non-renewable energy inputs were calculated to be 469.12 MJ ha-1 (3.88%) and 11610.03 MJ ha-1 (98.65%), respectively. The calculation shows that the total greenhouse gas emissions are 380.52 kgCO2-eq ha-1 and the greenhouse gas emission rate is 0.38 kgCO2-eq ha-1. Sesame production is highly profitable for the 2022-2023 production season in terms of energy use efficiency.

Sugarcane Burning: Why?

The sugarcane harvesting practices of farmers pose a recurring problem of burning the sugarcane fields every year, leading to the release of PM 2.5, which is hazardous to health and a matter of concern for all parties involved. The objective of this research is to investigate the causes of sugarcane burning by farmers. Data is collected through participatory observation methods and group discussions with a sample group of farmers in the provinces with the highest incidents of sugarcane field fires, namely Nakhon Ratchasima, Kalasin, and Khon Kaen in the northeastern region of Thailand during the 2021/2022 production season. Content analysis techniques are employed to identify the reasons behind the behavior of burning sugarcane. The findings reveal that sugarcane burning has been a long-standing practice among farmers, and the prevalence of burning has increased due to a shortage of labor for sugarcane cutting. The available machinery for sugarcane cutting is insufficient and unsuitable for the farmers' fields. Farmers who burn sugarcane fields are aware of the health impacts and have benefited from the government's measures to address the issue of sugarcane field fires. However, it is observed that the quantity of burnt sugarcane still exceeds the government's target, because burning sugarcane is a cost-effective, convenient, and rapid method. It is found that penalizing farmers at a rate of 30 Baht per ton of burnt sugarcane and providing assistance at a rate of 120 Baht per ton of fresh-cut sugarcane does not sufficiently motivate farmers to change their sugarcane burning behavior.

Optimal decisions for green products with advanced payment scheme and selling price‐dependent demand under interval uncertainty

In the current competitive market, green products are becoming more and more in demand across all customer demographics due to environmental contamination. Consequently, this has a direct impact on the notable rise in product demand. Conversely, a product cannot be used or repurposed if its maximum useful life has already elapsed. Therefore, the product's maximum lifespan plays a crucial role in inventory management. Advance payment is a critical component of the supplier–retailer relationship for a seasonal product with high demand. By integrating these issues, an inventory model for perishable goods is created, wherein the demand for the good is impacted by both its selling price and its green level. The model also includes linearly time‐dependent holding costs. According to this model, product greenness has an increasing effect on per‐unit costs. Different numerical examples are studied for supporting this model. Optimality of the objective function is shown graphically as well as numerically with the help of MATHEMATICA software. Finally, a fruitful conclusion is reached after performing a sensitivity analysis and visually depicting the impact of changing various factors.

Identification and Characterization of a Virulent Meloidogyne incognita Population Breaking Tomato Mi-1-Mediated Resistance in Indiana

High-tunnel production is increasing rapidly in the US due to its effectiveness in extending production seasons. Tomato is considered one of the most profitable crops grown in high tunnels. The elevated soil temperature and constant soil moisture in high tunnels lead to the buildup of root-knot nematodes (RKNs). Growing RKN-resistant tomato cultivars or grafting onto RKN-resistant tomato rootstocks is considered effective in managing RKNs. However, all of the RKN-resistant tomato cultivars or rootstocks carry the same resistance gene, Mi-1. This lack of diversity in resistance has led to the emergence of virulent RKN populations breaking tomato Mi-1 resistance. Here, we identified and characterized a virulent population of Meloidogyne incognita from a high tunnel in Indiana. The M. incognita population was confirmed as being able to infect and reproduce on two resistant tomato cultivars, Better Boy and Early Girl, carrying the Mi-1 gene, under a controlled environment at 24 °C. To our knowledge, this is the first report of a virulent M. incognita population breaking Mi-1 resistance in Indiana. Virulent M. incognita populations overcoming Mi-1 resistance were previously reported in California and Georgia in the US. This work emphasizes the importance of regularly monitoring RKN population virulence to sustainably manage the pest.

1H NMR profiling and chemometric analysis for ripening and production characterization of Grana Padano cheese

Grana Padano (GP) cheese is a renowned PDO Italian cheese whose nutritional characteristics and market price are influenced by the ripening stage. In this work, it was demonstrated that the combined use of untargeted 1H NMR profiling and chemometric analysis can be used as a powerful tool to quantitatively characterize GP ripening and production, focusing on both aqueous and lipid fractions. An initial exploratory analysis revealed substantial variations in the aqueous fraction attributable to aging time, year and season of production. Multivariate analysis was adopted to show these differences, mainly attributable to amino acids. In contrast, the lipid fraction analysis highlighted the impact of production season on fatty acid unsaturation, influenced by feed variations. As regards the production process, this study focuses on the variations induced by bactofugation. In this respect, the aqueous fraction was found to be extensively influenced by this centrifugation step, affecting compounds crucial to organoleptic characteristics.

Hydraulic analysis for assessing environmental flow selection and ecological model formulation

AbstractEcosystem management depends on transforming qualitative observations (e.g., slow‐moving shallow conditions provide nursery refugia for silvery minnow larvae) into management actions to increase habitat quantity or improve habitat quality. To be effective, decision metrics that are developed for management objectives should be validated with field observations. Model assumptions, precision and parameter importance can be refined by comparing the fidelity of selected parameters computed as habitat quality metrics and the correlation of these metrics to real‐world observations. Validated environmental metrics are more credible for management and can be compatible with ecosystem monitoring and project design processes. In this study, streamflow monitoring data and hydraulic modelling are used to quantify fish habitat extent for 15 years of spring runoff. The spring runoff event coincides with larval maturation to a free‐swimming juvenile phase for the silvery minnow, a critical period in Rio Grande habitat management. Different methods to estimate habitat availability (i.e., hydrology statistics, inundation extents based on hydraulic modelling and areal habitat availability based on different formulations of a habitat suitability index curve) were used to test the efficacy of different metrics relative to species population monitoring. This analysis finds that flow–ecology relationships based on hydraulic modelling or hydrology statistics are both effective and highly correlated to larval production. The investigation shows how seasonal hydrologic characterization and hydraulic discretization have varying levels of correlation with seasonal fish production. This study demonstrates how hydraulic modelling data and hydrologic characterization of riverine environments can be used to validate or develop conceptual ecological models.

Determinantes of the economic efficiency of white onion production (crystal ) in Nineveh Governorate for the production season 2022 ( a field study in Shekhan district )

Determinantes of the economic efficiency of white onion production (crystal ) in Nineveh Governorate for the production season 2022 ( a field study in Shekhan district )

Determinantes of the economic efficiency of white onion production (crystal ) in Nineveh Governorate for the production season 2022 ( a field study in Shekhan district )

Determinantes of the economic efficiency of white onion production (crystal ) in Nineveh Governorate for the production season 2022 ( a field study in Shekhan district )

Developments in Employment Opportunities: Indispensable in Sustaining one’s Living Conditions in a Satisfactory Manner

The individuals, belonging to rural communities have agriculture and farming practices as their primary occupations. But through getting engaged in these occupations, they are unable to generate sufficient income. They are engaged in these practices only during the productive season, whereas, during the rest of the year they remain unemployed. Hence, in order to lead to progression of rural individuals and communities, one needs to get engaged in employment opportunities. These are facilitating in not only generating income, but rural individuals are able to hone their competencies, abilities and aptitude. One of the important aspects is, rural individuals are being well-prepared to generate income and bring about improvements in their overall quality of lives. This is facilitated through getting engaged in employment opportunities. Furthermore, there is a need to formulate different types of programs, which are facilitating in leading to up-gradation of employment opportunities within rural communities. In addition, there are establishment of different types of industries and factories within rural communities, which are facilitating in promoting employment opportunities. One important aspects is, one needs to be well-versed in terms of job duties and methodologies to put these into practice. Therefore, it is well-understood, developments in employment opportunities is indispensable in sustaining one’s living conditions in a satisfactory manner. The main concepts that are taken into account in this research paper are, measures to be implemented in promoting developments in employment opportunities within rural communities and factors taken into account by rural individuals to implement employment opportunities appropriately.

Effect of Input Subsidy Reduction on Greenhouse Emission Reduction Potential in Paddy Production Systems in Karnataka State of India

Increasing concerns and call for reduction in Greenhouse gas (GHG) emission have necessitated the search for broader and all-inclusive policy initiatives, extending into agricultural production, where high carbon energy inputs are used. One classical policy strategy for GHG emission reduction, has been taxation. However, given the critical role of agriculture, especially in developing economies, policies that directly or indirectly increase agricultural inputs costs and reduce their demand require stronger theoretical, conceptual and empirical support to ensure that while agri-environmental quality is promoted, welfare of farming households, food security and overall economic growth are not compromised. Using paddy production in Karnataka state in India, the study assessed effects of agricultural input taxation (reduction in rice input subsidy) on future demand for such inputs and their effect on GHG emission reduction, vis-a-viz production and welfare losses. In microeconomic modelling framework, we applied quadratic almost ideal demand system and stochastic efficiency functions in the analysis of the data. Data for the study, a micro-level farm data, was obtained from Cost of Cultivation Scheme (CSS) for irrigated and non-irrigated production systems, covering the period 2009 -2018 production seasons. Specifically, the study used three future tax regime scenarios- 10%, 20% and 30% input subsidy reduction rates, to model an optimum greenhouse emission reduction potential. The results revealed that inputs evaluated were normal with inelastic demand functions; many input coefficients implied significant complementary relationships; irrigated paddy production system had higher estimates of GHG emissions. Input taxation (reduction in subsidy) under all the three scenarios effectively, resulted in declined inputs consumption patterns, and subsequently led to significant decrease in greenhouse emissions. The highest GHG emission reduction potential was observed in irrigated farming system. Greenhouse emission reduction potential was optimal at moderate subsidy reduction policy rate of 10%. It is recommended that, given the inelastic estimates derived, moderate tax (reduction in subsidy) policy option on inputs would yield effective greenhouse mitigation with appropriate compensation through effective integrative schemes.

Machine learning modeling to predict causes of infectious abortions and perinatal mortalities in cattle

A plethora of infectious and non-infectious causes of bovine abortions and perinatal mortalities (APM) have been reported in literature. However, due to financial limitations or a potential zoonotic impact, many laboratories only offer a standard analytical panel, limited to a preestablished number of pathogens. To improve the cost-efficiency of laboratory diagnostics, it could be beneficial to design a targeted analytical approach for APM cases, based on maternal and environmental characteristics associated with the prevalence of specific abortifacient pathogens. The objective of this retrospective observational study was to implement a machine learning pipeline (MLP) to predict maternal and environmental factors associated with infectious APM. Our MLP based on a greedy ensemble approach incorporated a standard tuning grid of four models, applied on a dataset of 1590 APM cases with a positive diagnosis that was achieved by analyzing an extensive set of abortifacient pathogens. Production type (dairy/beef), gestation length, and season were successfully predicted by the greedy ensemble, with a modest prediction capacity which ranged between 63 and 73 %. Besides the predictive accuracy of individual variables, our MLP hierarchically identified predictor importance causes of associated environmental/maternal characteristics of APM. For instance, in APM cases that happened in beef cows, season at APM (spring/summer) was the most important predictor with a relative importance of 24 %. Furthermore, at the last trimester of gestation Trueperella pyogenes and Neospora caninum were the most important predictors of APM with a relative importance of 22 and 17 %, respectively. Interestingly, herd size came out as the most relevant predictor for APM in multiparous dams, with a relative importance of 12 %. Based on these and other mix of predicted environmental/maternal and pathogenic potential causes, it could be concluded that implementing our MLP may be beneficial to design a more cost-effective, case-specific diagnostic approach for bovine APM cases at the diagnostic laboratory level.

Spatial and temporal distribution of Scirtothrips dorsalis (Thysanoptera: Thripidae) and their natural enemies in Florida strawberry fields.

Given the recent invasion of Scirtothrips dorsalis Hood in North America, there is limited information regarding their distribution and population dynamics in cultivated small fruit crops. Therefore, we investigated the spatial and temporal distribution of S. dorsalis and their natural enemies in commercially produced strawberry fields in Florida. During 2 consecutive strawberry production seasons, 4 and 6 geographically separated strawberry fields were sampled and were divided into grids with 30-40 sampling points per field. At each sampling point, 4-5 leaf and flower samples were collected, and sticky traps were deployed. We quantified the occurrence of S. dorsalis as well as potential natural enemies, including Orius spp., Geocoris spp., and other predators such as long-legged flies. During both years, most of the S. dorsalis and natural enemies were found on field borders, and counts progressively diminished further into the interiors of plots and away from field edges. Cluster and outlier analysis revealed that S. dorsalis formed statistically significant clusters and that these "hot spots" remained in the same general locations throughout the season. There was a strong relationship between the occurrence of natural enemies and the presence of S. dorsalis, but the number of natural enemies was generally low compared to S. dorsalis. Our results indicate that targeting field borders for chemical control or planting strawberries away from natural areas containing potential alternative hosts for thrips may be an effective strategy for reducing agricultural inputs; however, future field assessments are needed to determine if these methods could replace the treatment of entire fields.

A comprehensive study on the spatial and temporal variation of BTEX and asbestos in the northwest of Iran: Human risk assessment

Substances like asbestos and other air pollutants, such as BTEX (benzene, toluene, ethylbenzene, and xylene), are hazardous compounds due to their adverse effects on human health. This study aims to investigate the levels, seasonal variations, spatial distribution, potential sources, and associated health risks associated with BTEX compounds and asbestos fibers in the ambient air of Tabriz. Air samples were taken at 16 different locations during the 2020–2021 period. Glass containers with charcoal were used for sample collection, and the BTEX content was determined using the GC-FID method. Phase-contrast microscopy (PCM) analysis was conducted with a low-volume peripheral pump for asbestos fiber sampling. The results showed that the average concentration of ∑BTEX was 37.94 and 27.98 μg/m3 in autumn and spring, respectively. The same parameter was 2.26 and 1.68 f/L for asbestos in the autumn and winter, respectively. The contribution of BTEX to ozone formation potential (OFP) in the research area showed that xylene and toluene were the major contributors to ozone production in different seasons. The risk of exposure to benzene compounds was 24 × 10−4 in children and 55.9 × 10−4 in adults, while the risk of exposure to ethylbenzene was 3.78 × 10−4 in children and 3.25 × 10−4 in adults. The estimated lifetime cancer risk was found to be the highest for benzene, followed by ethylbenzene. The estimated cancer risk for benzene and ethylbenzene exceeded the threshold values set by EPA, which signals a significant carcinogenic risk due to exposure to these substances in the ambient air of Tabriz. According to the EPA guidelines, the low carcinogenicity risk levels are between 10−4 and 10−6. According to the findings for the exposure to asbestos fibers, the maximum values of excess cancer risk (ECR) and estimated lifetime cancer risk (ELCR) were observed in the 16–30 age range across all locations, suggesting increased exposure to asbestos fibers compared to other age groups.

Conservation Agricultural Practices Influencing the Seasonal Weed Dynamic and Productivity of Wheat in the Trans Indo-Gangetic Plains of India

Conservation Agricultural Practices Influencing the Seasonal Weed Dynamic and Productivity of Wheat in the Trans Indo-Gangetic Plains of India

Skill assessment of seasonal forecasts of ocean variables

There is growing demand for seasonal forecast products for marine applications. The availability of consistent and sufficiently long observational records of ocean variables permits the assessment of the spatial distribution of the skill of ocean variables from seasonal forecasts. Here we use state-of-the-art temporal records of sea surface temperature (SST), sea surface height (SSH) and upper 300m ocean heat content (OHC) to quantify the distribution of skill, up to 2 seasons ahead, of two operational seasonal forecasting systems contributing to the seasonal multi-model of the Copernicus Climate Change Services (C3S). This study presents the spatial distribution of the skill of the seasonal forecast ensemble mean in terms of anomaly correlation and root mean square error and compares it to the persistence and climatological benchmarks. The comparative assessment of the skill among variables sheds light on sources/limits of predictability at seasonal time scales, as well as the nature of model errors. Beyond these standard verification metrics, we also evaluate the ability of the models to represent the observed long-term trends. Results show that long-term trends contribute to the skill of seasonal forecasts. Although the forecasts capture the long-term trends in general, some regional aspects remain challenging. Part of these errors can be attributed to specific aspects of the ocean initialization, but others, such as the overestimation of the warming in the Eastern Pacific are also influenced by model error. Skill gains can be obtained by improving the trend representation in future forecasting systems. In the meantime, a forecast calibration procedure that corrects the linear trends can produce substantial skill gains. The results show that calibrated seasonal forecasts beat both the climatological and persistence benchmark almost at every location for all initial dates and lead times. Results demonstrate the value of the seasonal forecasts for marine applications and highlight the importance of representing the decadal variability and trends in ocean heat content and sea level.

Effects of spruce budworm defoliation on in-stream algal production and carbon use by food webs

Insect defoliation is a widespread cause of forest disturbance in Canada, and it has the potential to alter terrestrial carbon contributions to stream consumers and thus affect stream ecosystems. Although defoliation by spruce budworms ( Choristoneura fumiferana) is considered a natural disturbance with importance to forest succession, the magnitude and duration of outbreaks are increasing, and there is a growing need to understand their downstream consequences. To examine this, algal productivity and autochthonous (in-stream) energy supporting macroinvertebrate and fish consumers (using δ13C, δ15N) were examined in 12 streams in the Gaspé Peninsula, Québec, Canada, that ranged in watershed defoliation from spruce budworm. Hierarchical partitioning models were used to assess the contributions of watershed and stream variables to these endpoints. Total seasonal algal production ranged fourfold among sites, and cumulative defoliation was the strongest predictor. Consumers from streams with greater defoliation (cumulative or annual) had lower reliance on autochthonous carbon, despite increased algal production, and this effect was greater for brook trout than macroinvertebrates. These findings demonstrate for the first time that insect outbreaks—which alter forest structure and function—also similarly affect downstream aquatic ecosystems by causing changes in the production and contributions of carbon sources. This suggests that insect control strategies and forest management decisions should also consider implications for downstream aquatic ecosystems.

A Bayesian analysis of adaptation of mountain grassland production to global change

Abstract In mountains, grasslands managed for livestock production sustain local economies, culture and identity. However, their future fodder production is highly uncertain under climate change: While an extended growing season may be beneficial, more frequent and intense summer droughts could also reduce fodder quantity and quality. Land use and land cover (LULC) changes are another major driver of grassland biomass production, but combined effects of future land use transitions and climate change are rarely quantified. We modelled combined climate and LULC scenarios for grassland production of the Maurienne Valley (French Alps) by 2085. We built a Bayesian Belief Network (BBN) from long‐term grassland production monitoring data complemented with expert knowledge. We assessed the potential of two candidate adaptations, intensification as an incremental solution and silvopastoralism as a transformative solution to compensate combined impacts of two climate scenarios and three land use change scenarios. Total biomass production was far more sensitive to LULC than to climate scenarios. Production losses were largest under the conservation LULC scenario (−28% on average between 2020 and 2085), followed by the tourism development scenario (−7%) and the business‐as‐usual scenario (+3%). Climate change under representative concentration pathways (RCP) 8.5 altered the seasonality of production by increasing potential production from May to July while decreasing summer regrowth. Synthesis and applications: Changes in LULC are more decisive for global biomass production than climate change. However, under the most extreme climate change scenario (RCP8.5), the seasonal shift in production and increased interannual variability threaten the current grass‐based protected designation of origin (PDO) production system. Only the intensification adaptation solution showed significant gains in total biomass production. Still, the silvopastoralism would require less investment compared to the intensification and have a similar efficiency when assessing the gains of biomass by the surface concerned with adaptation solutions. Along with decreased total annual production due to decreasing grassland area compounded by more extreme climate change, the seasonal shift in production and increased interannual variability threaten the current grass‐based PDO production system. Further Bayesian modelling co‐developed with local stakeholders and experts could greatly contribute to adaptation planning of the regional production system.

Potatoes (Solanum tuberosum L.) grown at “Patata dell'alto Viterbese” PGI have different quality characteristics and storage responses

Four pre-selected potato cultivars (Solanum tuberosum L.) from the “Patata dell’Alto Viterbese” PGI area underwent physico-chemical and enzymatic characterization to assess their suitability for specific processing line. Key chemical parameters (reducing sugar content (RSC), total phenol content (TPC), dry matter (DM), physical attributes (firmness), physico-chemical aspects (color, browning development), and enzymatic factors (polyphenol oxidase enzyme activity, PPO) were analyzed at harvest and monthly during a 6-month storage period over two production seasons (2020 and 2021). The results of one-way within-subject ANOVA and Principal Component Analysis (PCA) highlighted the superior attributes of the ‘Fontane’ cultivar for the processing industry, particularly for frying applications (e.g., chips, French fries, etc.). In comparison to other tested cultivars, ‘Fontane’ exhibited: i) the highest DM (> 200 g kg−1), ii) the lowest TPC and RSC, iii) the greatest firmness, iv) low susceptibility to browning, and v) high tolerance to Low-Temperature Sweetening (LTS). The ‘Jelly’ cultivar displayed favorable attributes for versatile use, suitable for both fresh market uses (roasting, homemade “gnocchi”, etc.) and industrial applications (fresh-cut or dried potato). It demonstrated high DM content (200 g kg−1) and firmness, the lowest PPO activity, good TPC, but higher RSC than ‘Fontane’. However, elevated RSC for ‘Jelly’ renders it less suitable for industrial frying. ‘Constance’ and ‘Gaudi’ exhibited positive traits for fresh market use such as boiling and steaming, with moderate to low DM content and firmness. Nonetheless, both cultivars displayed low tolerance to LTS, and ‘Gaudi’ exhibited the poorest processing properties, showing the highest susceptibility to browning.

Observation-Based Ozone Formation Rules by Gradient Boosting Decision Trees Model in Typical Chemical Industrial Parks

Ozone pollution in chemical industrial parks is severe and complicated and is significantly influenced by pollutant emissions and meteorological parameters. In this study, we innovatively investigated the formation rules of ozone by using observation-based analyses and a gradient-boosting decision tree (GBDT) model, focusing on a typical chemical industrial park located in the Yangtze River Delta of China. The results revealed that ozone concentration was positively correlated with temperature while negatively correlated with NO2 concentration and relative humidity (RH). Ozone pollution was predominantly observed from April to October (M4–10). The optimized GBDT model was subsequently utilized to establish a specific and quantifiable relationship between each single dominant impact factor (RH, NO2, temperature, and PM2.5) and ozone within a complex and uncertain multi-factor context during M4–10. Detailed discussions were conducted on the reaction rate of ozone-related to different levels of RH and temperature. The accumulation of ozone was favored by high temperature and low RH, with the maximum ozone concentration observed at the RH of 50% and the temperature of 35 °C. The NO2-O3 change curve exhibited distinct phases, including a period of stability, gradual increase, rapid increase, and equilibrium. During the second and third periods, the ratio of ozone production to NO2 consumption was 0.10 and 2.73, respectively. Furthermore, there was a non-monotonic relationship between variations in ozone concentration and PM2.5 concentration. Hence, it is imperative to implement fine control strategies in the park, such as adopting seasonal production strategies, implementing targeted measures for controlling NOx and active VOCs, and employing special control methods during periods of high temperature. This study provides aid in achieving effective management of localized ozone pollution and ensuring compliance with air quality standards.