Spatial reduction algorithm for atmospheric chemical transport models

Machine learning based quantification of VOC contribution in surface ozone prediction

The prediction of surface ozone is essential attributing to its impact on human and environmental health. Volatile organic compounds (VOCs) are crucial in driving ozone concentration; particularly in urban areas where VOC limited regimes are prominent. The limited measurements of VOCs, however, hinder assessing the VOC-ozone relationship. This work applies machine learning (ML) algorithms for temporal forecasting of surface ozone over a metropolitan city in India. The availability of continuous VOCs measurement data along with meteorology and other pollutants during 2014-2016 makes it possible to deduce the influence of various input parameters on surface ozone prediction. After evaluating the best ML model for ozone prediction, simulations were carried out using varied input combinations. The combination with isoprene, meteorology, NO_x, and CO (Isop + MNC) was the best with RMSE 4.41 ppbv and MAPE 6.77%. A season-wise comparison of simulations having all data, only meteorological data and Isop + MNC as input showed that Isop + MNC simulation gives the best results during the summer season (RMSE: 5.86 ppbv, MAPE: 7.05%). This shows the increased ability of the model to capture ozone peaks (high ozone during summer) relatively better when isoprene data is used. The overall results highlight that using all available data doesn't necessarily give best prediction results; also critical thinking is essential when evaluating the model results.

Emission and spatialized health risks for trace elements from domestic coal burning in China

Residential coal combustion (RCC) emission exhibited obvious daily variation, while no real-time estimation of air pollutants from RCC has been reported, as the shortages of corresponding activity dataset and emission factors with high time resolution. A real-time monitoring platform for RCC emission was established. Hourly emission factors of 18 typed of TEs from eleven kinds of chunk coals and nine kinds of honeycomb coals burning in China were obtained. The monthly and hourly coal consumption amounts were calculated with reference and our field survey. Then the hourly TEs emission inventories from RCC were established in China. GEOS-Chem and Risk Quotients Models were utilized to map the spatialized health risks of hazardous elements, including the gridded hazard index and carcinogenic risk. The result indicated that the EFs of TEs would be underestimated if the tests only consider flaming conditions. Cu, K, Ca, Zn, and Co were the top five elements from RCC, with corresponding emission amounts as 1397.7, 1054.0, 676.0, 623.5 and 420 tons in 2017, respectively. K, Ti, Fe, Sn, and Sb showed hourly peak values under flaming dominated periods, accounting for 48.2%, 45.9%, 31.8%, 42.8%, and 33.8% of their daily emissions. Other elements (e.g., V, Co, As, Hg and Pb) exhibited higher emissions under smoldering dominated period in nighttime, accounting for 22.2%, 32.9%, 27.6%, 34.7%, and 28.4% of their daily emissions. TEs emission from RCC closely follows the habits of human daily cooking and heating activity. The national HI were lower than the acceptable level (HI ≤ 1) except Sichuan Province (up to 1.2). Higher carcinogenic risks (≥1 × 10^-6) occurred in parts of Sichuan, Shanxi, Hunan and Hubei, which were up to 2.0 × 10^-5. The high-resolution TEs emission inventories could be useful for future modeling works on the formation and evolution of air pollution and are helpful for human exposure assessment.

Toward Clean Residential Energy: Challenges and Priorities in Research

Solid fuels used for cooking, heating, and lighting are major emission sources of many air pollutants, specifically PM_2.5 and black carbon, resulting in adverse environmental and health impacts. At the same time, the transition from using residential solid fuels toward using cleaner energy sources can result in significant health benefits. Here, we briefly review recent research progress on the emissions of air pollutants from the residential sector and the impacts of emissions on ambient and indoor air quality, population exposure, and health consequences. The major challenges and future research priorities are identified and discussed.

Sources and reactivity of NMHCs and VOCs in the atmosphere: a review

Nonmethane hydrocarbons (NMHCs) and volatile organic compounds (VOCs) are important species present in the environment, which results in alteration of the chemistry of atmosphere. On the global scale natural emissions of NMHCs and VOCs exceed anthropogenic emissions, although anthropogenic sources usually dominate within urban areas. Among the natural sources, vegetation is the dominant source. Oceanic and microbial production of these species is minimal as compared to other sources of input. Isoprene and terpenes are main species of NMHCs which are emitted from plants as a protective mechanism against temperature stress tolerance and protection from ravages of insects and pests. The major anthropogenic sources for NMHCs emissions are biomass burning and transportation. NMHCs play a significant role in ozone (O(3)) production in the presence of adequate concentration of oxides of nitrogen in the atmosphere. The production of O(3) is based on Maximum Incremental Reactivity (MIR) of NMHCS and VOCs. The compound's MIR multiplied by molecular weight gives Relative Ozone Productivity (ROPi). To check the reliability of current methods of measuring the NMHCs the Nonmethane Hydrocarbon Inter-comparison Experiment (NMHICE) had been designed. The sample of known composition and unknown concentration of different hydrocarbons was supplied to different laboratories worldwide and less than 50% laboratories correctly separated the unknown mixture. Atmospheric scientists throughout the world are evaluating current analytical methods being employed and are trying to correct the problems to ensure quality control in hydrocarbon analysis.