Search NASA⌕ Search

SEARCH · Search NASA

Results for “pollutant”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Assessment of urban aerosol pollution over the Moscow megacity by the MAIAC aerosol product

We estimated the distribution of aerosol optical thickness (AOT) with a spatial resolution of 1 km over the Moscow megacity using the MAIAC aerosol product based on MODIS satellite data (Lyapustin et al., 2018) for the warm period of the year (May–September, 2001–2017). AERONET (Aerosol Robotic Network)-based validation of satellite estimates near the city centre at Moscow_MSU_MO and over the Moscow suburbs at Zvenigorod revealed that MAIAC AOT at 0.47 μm is in agreement with AERONET AOT though underestimated by 0.05–0.1 for AOT < 1 and overestimated for smoke conditions with AOT > 1. The MAIAC AOT biases were almost the same for the Moscow_MSU_MO and Zvenigorod AERONET sites, which indicated that the MAIAC algorithm effectively removed the effect of the bright urban surface in the city centre. For the ground-based measurements, the difference between annual median AOT at Moscow_MO_MSU and Zvenigorod (∆AOT) varied within -0:002 to +0:03, with statistically significant positive bias for most years, and an average ∆AOT was about 0.02. According to the MAIAC dataset, the ∆AOT varied within ±0:01 and was not statistically significant. The ∆AOT started decreasing recently due to intensive urban development of the territory around Zvenigorod and the decrease in pollutant emissions in Moscow, which is mainly caused by the environmental regulations. According to the MAIAC dataset, the most pronounced spatial AOT differences over the territory of Moscow were observed at the 5% quantile level, where they reached 0.05–0.06 over several locations and could be attributed to the stationary sources of aerosol pollution, for example, large areas of construction sites, aerosol pollution from roads and highways, or agriculture activities. The differences between the maximum and the mean AOT for different quantiles, except the 95% quantile, within the Moscow region, were about 0.02–0.04, which could be attributed to the local aerosol sources. The application of the MAIAC algorithm over the whole Moscow region has revealed a decreasing AOT trend over the centre of Moscow and an increasing trend over the “New” Moscow territory which experienced an intensive build-up and agricultural development.

urban aerosol pollution↗
NASA NTRS2021

The impact of Los Angeles Basin pollution and stratospheric intrusions on the surrounding San Gabriel Mountains as seen by surface measurements, lidar, and numerical models

In this work, the impact of Los Angeles Basin pollution transport and stratospheric intrusions on the surface ozone levels observed in the San Gabriel Mountains is investigated based on a combination of surface and lidar measurements as well as WRF-Chem (Weather Research and Forecasting with Chemistry) and WACCM (Whole Atmosphere Community Climate Model) runs. The number of days with observed surface ozone levels exceeding the National Ambient Air Quality Standards exhibit a clear seasonal pattern, with a maximum during summer, when models suggest a minimum influence of stratospheric intrusions and the largest impact from Los Angeles Basin pollution transport. Additionally, measured and modeled surface ozone and PM10 were analyzed as a function of season, time of the day, and wind direction. Measurements and models are in good qualitative agreement, with maximum surface ozone observed for southwest and west winds. For the prevailing summer wind direction, slightly south of the ozone maximum and corresponding to south-southwest winds, lower ozone levels were observed. Back trajectories suggest that this is associated with transport from the central Los Angeles Basin, where titration limits the amount of surface ozone. A quantitative comparison of the lidar profiles with WRF-Chem and WACCM models revealed good agreement near the surface, with models showing an increasing positive bias as function of altitude, reaching 75 % at 15 km above sea level. Finally, three selected case studies covering the different mechanisms affecting the near-surface ozone concentration over the San Gabriel Mountains, namely stratospheric intrusions and pollution transport, are analyzed based on surface and ozone lidar measurements, as well as co-located ceilometer measurements and models.

Impact↗
NASA NTRS2022

Global Premature Mortality By Dust and Pollution PM 2.5 Estimated From Aerosol Reanalysis of the Modern-Era Retrospective Analysis for Research and Applications, Version 2

This study quantifies global premature deaths attributable to long-term exposure of ambient PM 2.5 , or PM 2.5 -attributable mortality, by dust and pollution sources. We used NASA’s Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) aerosol reanalysis product for PM 2.5 and the cause-specific relative risk (RR) from the integrated exposure-response (IER) model to estimate global PM2.5-attributable mortality for five causes of deaths, namely ischaemic heart disease (IHD), cerebrovascular disease (CEV) or stroke, lung cancer (LC), chronic obstructive pulmonary disease (COPD), and acute lower respiratory infection (ALRI). The estimated yearly global PM 2.5 -attributable mortality in 2019 amounts to 2.89 (1.38–4.48) millions, which is composed of 1.19 (0.73–1.84) million from IHD, 1.01 (0.35–1.55) million from CEV, 0.29 (0.11–0.48) million from COPD, 0.23 (0.14–0.33) million from ALRI, and 0.17 (0.04–0.28) million from LC (the numbers in parentheses represent the estimated mortality range due corresponding to RR spread at the 95% confidence interval). The mortality counts vary with geopolitical regions substantially, with the highest number of deaths occurring in Asia. China and India account for 40% and 23% of the global PM 2.5 -attributable deaths, respectively. In terms of sources of PM 2.5 , about 22% of the global all-cause PM 2.5 -attributable deaths are caused by desert dust. The largest dust attribution is 37% for ALRI. The relative contributions of dust and pollution sources vary with the causes of deaths and geographical regions. Enforcing air pollution regulations to transfer areas from PM 2.5 nonattainment to PM2.5 attainment can have great health benefits. Being attainable with the United States air quality standard (AQS) of 15 μg/m 3 globally would have avoided nearly 40% or 1.2 million premature deaths. The most recent update of PM 2.5 guideline from 10 to 5 μg/m 3 by the World Health Organization (WHO) would potentially save additional one million lives. Our study highlights the importance of distinguishing aerodynamic size from geometric size in accurately assessing the global health burden of PM 2.5 and particularly for dust. A use of geometric size in diagnosing dust PM 2.5 from the model simulation, a common approach in current health burden assessment, could overestimate the PM 2.5 level in the dust belt by 40–170%, leading to an overestimate of global all-cause mortality by 1 million or 32%.

PM2.5↗
DOE OSTI2020

Air Pollutant Emissions and Regulatory Implications of Co-Processing Raw Bio-Oil in U.S. Petroleum Refineries

Pyrolysis oil, often referred as bio-oil or biocrude, has attracted considerable attention because it has higher energy density and carbon content compared to the raw biomass. Using pyrolysis oil derived from low cost and underutilized biomass to produce renewable hydrocarbon fuels provides a viable link between the agriculture/forestry and (petro-) chemical industry. Co-processing bio-oil with vacuum gas oil (VGO) in petroleum refinery is appealing due to the relatively low capital requirement to retrofit refinery and the compatibility of fuel products with existing infrastructure. In order to implement co-processing, a petroleum refinery would need to consider several process modifications and therefore could be subject to varying levels of air permitting requirements based on bio-oil co-processing ratio, co-processing capacity in existing units, the amount of regulated pollutants expected to be emitted, among other factors. This analysis considers co-processing 5% (by weight) of raw bio-oil with VGO in the fluidized catalytic cracking (FCC) unit(s) in a petroleum refinery. We estimate the potential increase in emissions of regulated air pollutants resulting from the modifications required to implement bio-oil co-processing and evaluate the regulatory and permitting implications for three FCC size categories in the U.S. refineries, which could co-processes raw bio-oil to produce partially renewable transportation fuels. We also assess technically feasible emission control options petroleum refineries could adopt to avoid being subject to major source permitting requirements if the estimated increase in regulated air pollutant emission exceeds the applicable threshold for major modifications. Insights from our analysis can help overcome challenges and risks associated with timely obtaining air permits required to implement bio-oil co-processing in existing refineries. Our analysis also provides needed information for decision makers (e.g., local air quality agencies) to understand the potential air quality implications for retrofitting refineries to co-process bio-oil, particularly in areas with high concentration of petroleum refineries.

09 BIOMASS FUELS↗
DOE OSTI2022

Superhydrophobic Phosphonium Modified Robust 3D Covalent Organic Framework for Preferential Trapping of Charge Dispersed Oxoanionic Pollutants

Abstract Charge dispersed and less hydrophilic anionic pollutants are often difficult to be preferentially captured by common cationic framework materials. A gamma radiation modification approach is employed to anchor a superhydrophobic phosphonium‐containing coating on a robust crystalline 3D covalent organic framework (COF). By regulating the surface hydrophobicity, the prepared 3DCOF‐ g ‐VBPPh 3 Cl is endowed with a strong affinity for charge dispersed and less hydrophilic oxoanions, such as MnO 4 − , TcO 4 − and ReO 4 − , to surmount the Hofmeister bias, which much favors remediation of oxoanionic pollutants in complex aqueous systems. Batch and column experiments with 3DCOF‐g‐VBPPh 3 Cl in both tap water and simulated groundwater are performed, and rapid sequestration is achieved with removal efficacy up to 99.995%, record‐high distribution coefficient of 1.0 × 10 8 mL g −1 , and desirable priority over competing anions such as Cl − , SO 4 2− , HCO 3 − , and NO 3 − , confirming promise for remediation of charge dispersed anionic pollutants. Theoretical calculations reveal a mechanism of preferential capture based on electrostatic and dispersion interaction between charge dispersed anions and 3DCOF‐g‐VBPPh 3 Cl that effectively competes with solvation of the aqueous anions.

Wang, Yue↗
DOE OSTI2023

Experimental and numerical investigation of flame stabilization and pollutant formation in matrix stabilized ammonia-hydrogen combustion

Ammonia (NH 3 ) is a carbon-free fuel that offers an attractive alternative for reducing greenhouse gas emissions. However, the slow flame speed, low heating value, and emissions of nitrogen-containing pollutants present significant issues for practical combustion applications. To address these issues, we investigate the use of matrix stabilized combustion. In this type of burner, combustion is performed within an inert porous ceramic foam, heat is recirculated by solid conduction and radiation, which enhances flame speed and combustion stabilization, thereby permitting combustion over a wide range of equivalence ratio conditions. We present a new porous media burner (PMB) capable of stabilizing NH 3 /air flames at ambient conditions. An extensive experimental characterization of the stability of this burner is conducted with up to 30% by volume of hydrogen (H 2 ) in the fuel stream. A 15:1 turndown ratio is demonstrated, with a high thermal power density of 62 MW m -3 . Concentrations of NO, unburnt NH 3 , and H 2 in the exhaust stream are measured. Two regimes are identified for low NO operation: rich and very lean. For rich conditions, NO emissions decrease with increasing equivalence ratio and decreasing H 2 blending. Unburnt NH 3 emissions follow opposite trends. These measurements are complemented by simulations in which the burner is represented by a coupled solid-gas reactor network. In conclusion, this model captures the burner’s pollutant emissions to good accuracy and is used to analyze the mechanisms of pollutant formation.

42 ENGINEERING↗
DOE OSTI2022

Win-win transportation strategies for India: Linking air pollution and climate mitigation

Here, this article analyzes road transport in India to explore linkages between air pollution and climate change policies in the transportation sector. Five teams modeled five policy scenarios – fuel efficiency, electrification, alternative fuels, modal shifts, and moderation in transport demand – to explore which policy brings the largest synergetic effects in reducing carbon dioxide (CO 2 ) and particulate matter (PM 2.5 ) emissions. The teams also modeled the comprehensive scenario which included policy measures from individual scenarios. The paper concludes that all of the measures provide strong co-benefits in reducing air pollutant and CO 2 emissions. The modeling results show that increased energy efficiency of passenger and freight vehicles has the largest protentional for reducing both CO 2 and PM 2.5 emissions. It is possible to reach even a larger reduction of air pollutants and CO 2 emissions by combining several policy measures in the comprehensive scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Modeling atmospheric data and identifying dynamics Temporal data-driven modeling of air pollutants

Atmospheric modelling has recently experienced a surge with the advent of deep learning. Most of these models, however, predict concentrations of pollutants following a data-driven approach in which the physical laws that govern their behaviors and relationships remain hidden. Furthermore, with the aid of real-world air quality data collected hourly in different stations throughout Madrid, we present a case study using a series of data-driven techniques with the following goals: (1) Find systems of ordinary differential equations that model the concentration of pollutants and their changes over time; (2) assess the performance and limitations of our model using stability analysis; (3) reconstruct the time series of chemical pollutants not measured in certain stations using delay coordinate embedding results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Persistent Heavy Winter Nitrate Pollution Driven by Increased Photochemical Oxidants in Northern China

Nitrate is an increasingly important component of fine particulate matter (PM2.5) during winter in northern China. Past emission control has been ineffective in reducing winter nitrate. Here, we use extensive observations and a model with state-of-theart nitrogen chemistry to identify the key factors that control the nitrate formation in the heavily polluted North China Plain (NCP). In contrast to the previous view of weak winter photochemistry, we show that the O3 and OH productions are sufficiently high in winter to facilitate fast gas-phase and heterogeneous conversion of NOX to nitrate over the NCP. Increasing O3 and OH productions from higher precursor levels and fast ROX cycling accelerate the nitrate generation during heavy pollution. We find that the 31.8% reduction of NOX emissions from 2010 to 2017 in the NCP lowers surface nitrate by only 0.2% and even increases nitrate in some polluted areas. This is mainly due to the increase of O3 and OH (by~30%), which has subsequently increased the conversion efficiency of NOX to HNO3 (by 38.7%). Future control strategies for the winter haze should also aim to lower photochemical oxidants, via larger and synchronized NOX and VOCs emissions reduction, to overcome the effects of nonlinear photochemistry and aerosol chemical feedback.

Fu, Xiao↗
DOE OSTI2026

Ultranano Titania: Selectively Ridding Water of Persistent Organic Pollutants

Persistent organic pollutants, including the EPA's “dirty dozen”, are difficult to remove from water supplies due to their chemical stability. Here, we report a stable oxide photocatalyst, ultranano titania (d < 2 nm) doped with iron, Fe•TiUNP, that efficiently mineralizes multiple persistent pollutants including aromatic compounds plus common troublesome, difficult-to-oxidize intermediates such as formaldehyde and acetone, netting mineralization of persistent pollutants. Efficiency stems from a direct charge-transfer pathway. The key role of iron doping is to lower the reduction potential of the photogenerated electron so that it is insufficient to reduce water, thus eliminating competition from the hydrogen evolution reaction. The reduction potential of the localized electron is similarly insufficient to reduce quinone, enabling breaking aromaticity. Specific results for degrading acetone, phenol, benzoic acid, and 1,4-benzoquinone are reported.

alcohols↗
DOE OSTI2023

Significant contributions of trimethylamine to sulfuric acid nucleation in polluted environments

Abstract As one of the least understood aerosol processes, nucleation can be a dominant source of atmospheric aerosols. Sulfuric acid (SA)-amine binary nucleation with dimethylamine (DMA) has been recognized as a governing mechanism in the polluted continental boundary layer. Here we demonstrate the importance of trimethylamine (TMA) for nucleation in the complex atmosphere and propose a molecular-level SA-DMA-TMA ternary nucleation mechanism as an improvement upon the conventional binary mechanism. Using the proposed mechanism, we could connect the gaseous amines to the SA-amine cluster signals measured in the atmosphere of urban Beijing. Results show that TMA can accelerate the SA-DMA-based new particle formation in Beijing by 50–100%. Considering the global abundance of TMA and DMA, our findings imply comparable importance of TMA and DMA to nucleation in the polluted continental boundary layer, with probably higher contributions from TMA in polluted rural environments and future urban environments with controlled DMA emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Impact of truck electrification on air pollution disparities in the United States

Electrifying heavy-duty trucks reduces on-road diesel emissions but shifts the burden of supplying energy to power-generation facilities. The combined effect of Inflation Reduction Act investments in grid decarbonization and truck electrification will alter the magnitude and distribution of air pollution burdens across the United States. These investments are intended to facilitate a just energy transition, with 40% of the benefits flowing to disadvantaged communities per the Justice40 Initiative. Here we evaluate the combined effects of Inflation Reduction Act grid decarbonization and truck electrification investments on a national scale to determine whether the air pollution benefits would meet this 40% goal for both disadvantaged communities and the most exposed racial–ethnic groups. We find that truck electrification and decarbonization reduce air-pollution-related premature mortality in disadvantaged communities. However, the relative disparity between disadvantaged and non-disadvantaged communities increases, suggesting that a disproportionate share of benefits accrue to non-disadvantaged communities. Whereas absolute disparity in grid emissions decreases over time for all racial–ethnic groups, relative disparity remains largely unchanged, with Black populations being the most exposed. Electrifying drayage corridors would result in comparatively large health benefits for disadvantaged communities, suggesting that increasing targeted electrification investments in short-haul routes near urban areas (for example, ports) could be promising.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Anthropogenic sulfate aerosol pollution in South and East Asia induces increased summer precipitation over arid Central Asia

Precipitation has increased across the arid Central Asia region over recent decades. However, the underlying mechanisms of this trend are poorly understood. Here, we analyze multi-model simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP) to investigate potential drivers of the observed precipitation trend. We find that anthropogenic sulfate aerosols over remote polluted regions in South and East Asia lead to increased summer precipitation, especially convective and extreme precipitation, in arid Central Asia. Elevated concentrations of sulfate aerosols over remote polluted Asia cause an equatorward shift of the Asian Westerly Jet Stream through a fast response to cooling of the local atmosphere at mid-latitudes. This shift favours moisture supply from low-latitudes and moisture flux convergence over arid Central Asia, which is confirmed by a moisture budget analysis. High levels of absorbing black carbon lead to opposing changes in the Asian Westerly Jet Stream and reduced local precipitation, which can mask the impact of sulfate aerosols. This teleconnection between arid Central Asia precipitation and anthropogenic aerosols in remote Asian polluted regions highlights long-range impacts of anthropogenic aerosols on atmospheric circulations and the hydrological cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

rfasst: An R tool to estimate air pollution impacts on health and agriculture

Existing scientific literature shows that health and agricultural impacts attributable to air pollution are significant and should be considered in the integrated analysis of human and Earth-system interactions. The implementation of policies that affect the power sector, the composition of the vehicle fleet or the investments and deployment of different energy sources will in turn result in different levels of air pollution. Even though the various methodologies for estimating the impacts of air pollution, such as exposure-response functions, are extensively applied by the scientific community, they are normally not included in integrated assessment modeling outputs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Industrial Stormwater Pollution Prevention Plan (SWPPP) for SNL/CA Reporting Year 2022-2023

The Sandia National Laboratories, California (SNL/CA) site comprises approximately 410 acres and is located in the eastern portion of Livermore, Alameda County, California. The property is owned by the United States Department of Energy and is being managed and operated by National Technology & Engineering Solutions of Sandia, LLC. The facility location is shown on the Site Map(s) in Appendix A. This Stormwater Pollution Prevention Plan (SWPPP) is designed to comply with California’s General Permit for Stormwater Discharges Associated with Industrial Activities (General Permit) Order No. 2015-0122-DWQ (NPDES No. CAS000001) issued by the State Water Resources Control Board (State Water Board) (Ref. 6.1). This SWPPP has been prepared following the SWPPP Template provided on the California Stormwater Quality Association Stormwater Best Management Practice Handbook Portal: Industrial and Commercial (CASQA 2014). In accordance with the General Permit, Section X.A, this SWPPP contains the following required elements: Facility Name and Contact Information; Site Map; List of Significant Industrial Materials; Description of Potential Pollution Sources; Assessment of Potential Pollutant Sources; Minimum BMPs; Advanced BMPs, if applicable; Monitoring Implementation Plan (MIP); Annual Comprehensive Facility Compliance Evaluation (Annual Evaluation); and, Date that SWPPP was Initially Prepared and the Date of Each SWPPP Amendment, if Applicable.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Modeling Air Pollutant Emissions in the Provincial Level Road Transportation Sector in Korea: A Case Study of the Zero-Emission Vehicle Subsidy

South Korea has been suffering from high PM2.5 pollution. Previous studies have contributed to establishing PM2.5 mitigation policies but have not considered provincial features and sector-interactions. In that sense, the integrated assessment model (IAM) could complement the shortcomings of previous studies. IAM, capable of analyzing PM2.5 pollution levels at the provincial level in Korea, however, has not been developed yet. Hence, this study (i) expands on IAM which can represent provincial-level spatial resolution in Korea (GCAM-Korea) with air pollutant emissions modeling which focuses on the road transportation sector and (ii) examines the zero-emission vehicles (ZEVs) subsidy policy’s effects on PM2.5 mitigation using the expanded GCAM-Korea. Simulation results show that PM2.5 emissions decrease by 0.6–4.1% compared to the baseline, and the Seoul metropolitan area contributes 38–44% to the overall PM2.5 emission reductions. As the ZEVs subsidy is weighted towards the light-duty vehicle 4-wheels (LDV4W) sector, various spillover effects are found: ZEVs’ share rises intensively in the LDV4W sector leading to an increase in its service costs, and at the same time, driving bus service costs to become relatively cheaper. This, in turn, drives an increase in bus service demand and emissions discharge. Furthermore, this type of impact of the ZEVs subsidy policy does not reduce internal combustion engine vehicles (ICEVs) in freight trucks, although diesel freight trucks are a major contributor to PM2.5 emissions and also to NOx.

Roh, Minyoung↗
DOE OSTI2024

Hunting for Polluted White Dwarfs and Other Treasures with Gaia XP Spectra and Unsupervised Machine Learning

White dwarfs (WDs) polluted by exoplanetary material provide the unprecedented opportunity to directly observe the interiors of exoplanets. However, spectroscopic surveys are often limited by brightness constraints, and WDs tend to be very faint, making detections of large populations of polluted WDs difficult. In this paper, we aim to increase considerably the number of WDs with multiple metals in their atmospheres. Using 96,134 WDs with Gaia DR3 BP/RP (XP) spectra, we constructed a 2D map using an unsupervised machine-learning technique called Uniform Manifold Approximation and Projection (UMAP) to organize the WDs into identifiable spectral regions. The polluted WDs are among the distinct spectral groups identified in our map. We have shown that this selection method could potentially increase the number of known WDs with five or more metal species in their atmospheres by an order of magnitude. Such systems are essential for characterizing exoplanet diversity and geology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Dust pollution in China affected by different spatial and temporal types of El Niño

Dust is an important aerosol affecting air quality in China in the winter and spring seasons. Dust in China is potentially influenced by the interannual climate variability associated with El Niño. Here, the impacts of El Niño with different temporal and spatial types on dust pollution in boreal winter and spring in China and the potential mechanisms are investigated using a state-of-the-art Earth system model (E3SMv1). We find that the eastern Pacific (EP) and central Pacific (CP) El Niño both increase wintertime dust concentrations by 5–50 µg m –3 over central-eastern China. Due to a stronger wind and lower relative humidity, which favor dust emissions near sources, and a strengthened northwesterly and reduced precipitation, which are conducive to dust transport, dust concentrations during the CP El Niño are 5–20 µg m –3 higher in northern China than during the EP El Niño, although the changes are mostly insignificant. El Niño with a short duration (SD) increases boreal winter dust concentrations by 20–100 µg m –3 over northern China relative to the climatological mean, while there is a decrease of 5–50 µg m –3 during the long-duration (LD) El Niño, which is also related to the El Niño-induced changes in atmospheric circulation, precipitation, and relative humidity. In the following spring season, all types of El Niño events enhance dust over northern China, but only the increase during the LD El Niño is statistically significant, suggesting that the weaker intensity but longer duration of the LD El Niño events can significantly affect spring dust in China. Our results contribute to the current knowledge of the influence of El Niño on dust pollution, which has profound implications for air pollution control and dust storm prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗