Development of a COVID-19 Vulnerability Index (CVI) for the Counties and Residents of New Jersey, USA.

The coronavirus disease 2019, or COVID-19, has impacted countless aspects of everyday life since it was declared a global pandemic by the World Health Organization in March of 2020. From societal to economic impacts, COVID-19 and its variants will leave a lasting impact on our society and the world. During the height of the pandemic, it became increasingly evident that indices, such as the Center for Disease Control's (CDC) Social Vulnerability Index (SVI), were instrumental in predicting vulnerabilities within a community. The CDC's SVI provides important estimates on which communities will be more susceptible to 'hazard events' by compiling a variety of data from the U.S. Census and the American Community Survey. The CDC's SVI does not directly consider the susceptibility of a community to a global pandemic, such as the COVID-19 pandemic, due to the four themes and 15 factors that contribute to the index. Thus, the objective of this research is to develop a COVID-19 Vulnerability Index, or CVI, to evaluate a community's susceptibility to future pandemics. With 15 factors considered for CDC's SVI, 26 other factors were also considered for the development of the CVI that covered themes such as socioeconomic status, environmental factors, healthcare capacity, epidemiological factors, and disability. All factors were equally weighted to calculate the CVI based on New Jersey. The CVI was validated by comparing index results to real-world COVID-19 data from New Jersey's 21 counties and CDC's SVI. The results present a stronger positive linear relationship between the CVI and the New Jersey COVID-19 mortality/population and infection/population than there is with the SVI. The results of this study indicate that Essex County has the highest CVI, and Hunterdon County has the lowest CVI. This is due to factors such as disparity in wealth, population density, minority status, and housing conditions, as well as other factors that were used to compose the CVI. The implications of this research will provide a critical tool for decision makers to utilize in allocating resources should another global pandemic occur. This CVI, developed through this research, can be used at the county, state, and global levels to help measure the vulnerability to future pandemics.

Removal of pollutants from aqueous product of Co-hydrothermal liquefaction: Adsorption and isotherm studies.

Hydrothermal liquefaction (HTL) is an attractive technology for the conversion of wet waste into biofuel and co-HTL has been touted to increase the quality of products. However, the recovery of energy from wastewater byproduct called aqueous co-product (ACP) is limited due to the presence of toxic inhibitory substances. Adsorption has been countenanced to remove these toxic compounds but there has not been a distinct comprehensive adsorption isotherm study to explain the interaction between the adsorbate molecules and the adsorbent sites. This study investigated the sorption mechanism of oxidizable reducing pollutants measured as chemical oxygen demand (COD); heavy metals (boron and copper); and phenols from ACP samples obtained from co-HTL of brewery trub (BT), and primary sludge (PS) onto granular and powdered activated carbon (GAC and PAC). Conventional isotherm models such as Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich were used for data analysis. Results indicated that the adsorptive capacity (qe) of PAC was greater than GAC in COD adsorption (BT-1947 > 234; BTPS-617 > 245; PS-289 > 207), boron adsorption (BTPS-70 > 7; PS-53 > 49), copper adsorption (BT-5 > 1; BTPS-3 > 2; PS-1.3 > 1.1) and phenol adsorption (BT-1340 > 356; BTPS-1587 > 253; PS-460 > 245) in mg/g, µg/g, µg/g, and µg/g respectively. Comparing the adsorption of pollutants onto PAC and GAC, this study observed that PAC followed the Temkin, and Dubinin-Radushkevich models in the adsorption of the four pollutants while GAC followed the Freundlich and Langmuir models in the adsorption of phenol and copper, and Temkin, and Dubinin-Radushkevich in the adsorption of COD and boron. This study proved that combining feedstock in HTL (co-HTL) does not only change the quality of the ACP but also changes the dynamics of the adsorption isotherms. The Free Energy Change (ΔG0) result showed a spontaneous reaction in the adsorption of copper and phenol. This study presents an adsorption equilibrium information for the interpretation of adsorption isotherms for the overall improvement of adsorption mechanism pathways and the effective design of adsorption systems for the treatment of ACP.

Metal concentrations and distribution in paint waste generated during bridge rehabilitation in New York State.

Between 1950 and 1980, lead and chromium along with other metals have been used in paint coatings to protect bridges from corrosion. In New York State with 4500 bridges in 11 Regions 2385 of the bridges have been rehabilitated and subsequently repainted after 1989 when commercial use of lead based paint was prohibited. The purpose of this research was to address the concentration and distribution of trace metals in the paint waste generated during bridge rehabilitation. Using hypothesis testing and stratified sampling theory, a representative sample size of 24 bridges from across the state was selected that resulted in 117 paint waste samples. Field portable X-ray fluorescence (FP-XRF) analysis revealed metal concentrations ranged from 5 to 168,090 mg kg(-1) for Pb, 49,367 to 799,210 mg kg(-1) for Fe, and 27 to 425,510 mg kg(-1) for Zn. Eighty percent of the samples exhibited lead concentrations greater than 5000 mg kg(-1). The elevated iron concentrations may be attributed to the application of steel grit as an abrasive blasting material routinely used by state Departments of Transportation in the paint removal process. Other metals including Ba and Cr were observed in the paint waste as well. As a result of the paint formulation, metals were found to be associated in the paint waste (Pb correlated with Cr (r=0.85)). The elevated metal concentrations observed raises concern over the potential impact of leaching from this waste stream.

Field methods for rapidly characterizing paint waste during bridge rehabilitation.

For Department of Transportation (DOT) agencies, bridge rehabilitation involving paint removal results in waste that is often managed as hazardous. Hence, an approach that provides field characterization of the waste classification would be beneficial. In this study, an analysis of variables critical to the leaching process was conducted to develop a predictive tool for waste classification. This approach first involved identifying mechanistic processes that control leaching. Because steel grit is used to remove paint, elevated iron concentrations remain in the paint waste. As such, iron oxide coatings provide an important surface for metal adsorption. The diffuse layer model was invoked (logKMe=4.65 for Pb and logKMe=2.11 for Cr), where 90% of the data were captured within the 95% confidence level. Based on an understanding of mechanistic processes along with principal component analysis (PCA) of data obtained from field-portable X-ray fluorescence (FP-XRF), statistically-based models for leaching from paint waste were developed. Modeling resulted in 96% of the data falling within the 95% confidence level for Pb (R(2) 0.6-0.9, p ⩽ 0.04), Ba (R(2) 0.5-0.7, p ⩽ 0.1), and Zn (R(2) 0.6-0.7, p ⩽ 0.08). However, the regression model obtained for Cr leaching was not significant (R(2) 0.3-0.5, p ⩽ 0.75). The results of this work may assist DOT agencies with applying a predictive tool in the field that addresses the mobility of trace metals as well as disposal and management of paint waste during bridge rehabilitation.

Metal leaching from the bridge paint waste in the presence of steel grit.

The disposal of paint waste from bridge rehabilitation is a significant issue because of the potential release of contaminants and the consequent impact to human health and the environment. In this study, leaching behavior of paint waste was evaluated for 24 bridges in New York State. Although elevated Pb (5-168,090 mg kg(-1)) and other metal concentrations were observed in the paint samples, leaching experiments that included the toxicity characteristic leaching procedure (TCLP) and the multiple extraction procedure (MEP) revealed toxicity characteristic (TC) limits were not exceeded. The relatively low concentrations observed are attributed to the use of iron-based abrasives (steel grit) in the paint removal process. In this research, trace metals are hypothesized to be sequestered through interactions with iron oxide coatings formed on the steel grit surface resulting in reduced leachable concentrations. Through sequential extraction iron oxides were observed at 11.03% by wt and X-ray diffraction (XRD) further corroborated the presence of iron oxide coatings on the steel grit surface. Sequential extraction demonstrated that less than 6.8% of Pb, Cr, and Ba were associated with the exchangeable and carbonate forms, while greater contributions were found with iron oxides. The largest fraction, however, greater than 80%, was associated with the residual phase comprised of minerals in the paint including SiO2 and TiO2.

Environmental impact of metal and metalloid leaching from highway marking glass beads.

Recently, metals and metalloids have been observed at elevated concentrations in glass beads imported to the US. Average total concentrations in imported batches ranged from 103 to 683 mg kg(-1) for As, 62 to 187 mg kg(-1) for Sb, and 23 to 179 mg kg(-1) for Pb. The labile fraction associated with the glass beads resulted in leached concentrations as great as 538 µg L(-1) for As, 1092 µg L(-1) for Pb, and 160 µg L(-1) for Sb. Sequential extraction was conducted as well to better understand the form of metals and metalloids associated with the glass beads. Only 0.23% of As, 3.40% of Pb, 2.37% of Ba, and 1.92% of Mn were extracted in the exchangeable (As, Mn, and Ba) and the oxidizable forms (Pb), whereas greater than 97% of metals and metalloids present were associated with the glass matrix. Nonparametric statistics were applied to test total concentrations that resulted in exceedances in the groundwater quality criteria. Results demonstrated that the As, Pb, and Sb limits were exceeded for 98%, 58%, and 15% of the samples tested respectively suggesting a potential environmental impact to groundwater used as a drinking water source.