The impact of detailed spatial and temporal allocation of unconventional oil and gas development (UOGD) NOx emissions on predicted ozone formation was examined using hydraulic fracturing emissions in the Eagle Ford Shale region of Texas as a case study. Hydraulic fracturing occurs at specific well sites, lasting only 1-2 weeks prior to production. Four scenarios for spatial and temporal allocation of hydraulic fracturing NOx emissions were developed. In one scenario, NOx emissions were evenly distributed to all active wells in the Eagle Ford region, with continuous emissions throughout the year. In other scenarios, NOx emissions from hydraulic fracturing engines in Karnes County were allocated only to fractured wells, with durations ranging from 2 days to 2 weeks. In the month of August, predicted daily maximum of 8 h average (MDA8) O concentrations were consistently 6, 8, and 10 ppb higher over wide regions for the two-week, one-week, and two-day emission periods, respectively, compared to the annual county level distribution, demonstrating that detailed spatial and temporal allocation of NOx emissions in regions like the Eagle Ford Shale, with abundant biogenic VOCs, impacts predicted ozone formation.
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http://dx.doi.org/10.1021/acsestair.4c00077 | DOI Listing |
Environ Technol
March 2025
Vocational School of Technical Sciences, Agricultural Equipments and Machinery Program, Bursa Uludag University, Bursa, Turkey.
Increasing air pollutants significantly contributes to climate change, requiring innovative mitigation strategies. Microalgae provide a promising solution by absorbing CO₂ and pollutants like nitrogen oxides (NO), sulfur oxides (SO), and ammonia from agricultural and industrial emissions, while also generating biomass for biofuels and animal feed. This study investigated the effects of light intensity on the growth and biochemical composition of sp AQUAMEB-57, sp.
View Article and Find Full Text PDFJ Environ Manage
March 2025
School of Environment and Municipal Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China.
Landfill stale waste (LSW) poses considerable environmental issues, especially concerning methane emissions and the ecosystem contamination. This research investigates the potential for energy recovery and the emission profiles of LSW combustibles via steam gasification at various temperatures (700, 750, 800, and 850 °C) and combustion at 850 °C, utilizing a fixed-bed reactor and TG-DSC analysis. Our findings indicate that steam gasification conducted at 850 °C yields a high-quality syngas with a hydrogen concentration of 46.
View Article and Find Full Text PDFEnviron Int
March 2025
Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China.
Fine particulate matter (PM) pollution is a critical air quality concern which poses threats to public health. Despite strict air pollution control measures implemented in China since 2013, PM exceedances and region-wide PM episodes are still frequently observed in the Sichuan Basin (SCB) located in southwestern China. Here, we examine ambient PM pollution within the SCB from 2013 to 2020, focusing on emission sources, trends, and health outcomes.
View Article and Find Full Text PDFEnviron Pollut
March 2025
Sustainable Energy and Environmental Thrust, the Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511458, China.
Atmospheric chemical transport models (CTMs) are widely used in air quality management, but still have large biases in simulations. Accurately and efficiently identifying key sources of simulation biases is crucial for model improvement. However, traditional approaches, such as sensitivity and uncertainty analyses, are computationally intensive and inefficient, as they require multiple model runs.
View Article and Find Full Text PDFJ Environ Manage
March 2025
Institute of Thermal Power Engineering of Zhejiang University, Hangzhou, 310027, Zhejiang, China.
Owing to the complexity of municipal solid waste (MSW), flue gas composition and operating conditions, it is challenging to predict pollutant emissions accurately and control them intelligently in the MSW incineration process. This study uses a 750 t/d large-scale grate-type MSW incinerator as the research object. Based on a long short-term memory (LSTM) model, collaborative prediction (co-prediction) of multiple pollutants (HCl, SO, NO, and PM) emissions from MSW incinerator flue gas was achieved.
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