Search Results (24)

Latinx communities face disproportionate environmental injustices and are targeted due to systematic economic and political inequities. This research evaluates the ease at which links between industrial releases and risk of adverse health effects can be defined to influence policy change in Houston, TX. The Environmental Protection Agency (EPA)’s Toxic Release Inventory (TRI) is the most comprehensive public database on industrial facilities’ toxic chemical releases in the US. TRI is presented within a risk-based context through the Risk Screening Environmental Indicators (RSEI) scores. TRI and RSEI datasets for Houston in 2022 were assessed in QGIS to analyze chemical release and risk in neighborhoods using Community Tabulation Areas (CTAs), identifying demographics of communities facing disproportionate industrial releases and consequent potential health risks. Geospatial visualizations reflected Latinx communities to house the heaviest polluting industrial facilities in Houston. As a result, these communities face the highest potential risk of adverse health effects due to exposure to a multitude of chemicals—particularly 1,3-butadiene, benzene, and chromium—as reflected in cumulative RSEI scores. An analysis of TRI and RSEI datasets elucidates the burden of gathering and analyzing chemical release data in a public health context, reflecting why change beginning at the local level can be difficult for under-resourced Latinx communities facing industrial pollution. Improving the accessibility and utility of the EPA resources will provide a resource to advocate for data-driven policy change. Full article

A two-eyed seeing approach considered Indigenous knowledge and Western science towards eco–health, reconciliation and land back with Fort William First Nation (FWFN) in Ontario, Canada. To map traditional land use, occupancy, and ecological knowledge, we interviewed 49 FWFN members about their hunting, fishing, trapping, plant harvesting, cultural sites, and sacred gatherings on their ancestral land. Their traditional land use and occupancy includes more than 7.5 million ha of their ancestral land. The FWFN members reported many industrial impacts on their reserve and ancestral land. We analyzed the normalized difference vegetation index (NDVI) change over time on FWFN’s ancestral land and the Thunder Bay Pulp and Paper Mill (TBPP)’s National Pollutant Release Inventory data to investigate the FWFN members’ ecohealth concerns. The NDVI analysis revealed large tracts of degraded FWFN’s ancestral land due to logging areas, mining claims, settlements, and paper mills. Mining claims and greenstone belts occupy a quarter of the FWFN members’ ancestral land. The TBPP mill dumped pollution into the Kaministiquia River upstream and upwind of the FWFN community, exposing FWFN members to kilotons of cancerous and other toxic chemicals each year for over a century. Resource extraction and pollution in Northwestern Ontario negatively impacted the human health and ecosystem integrity of FWFN, requiring reconciliation by restoring damaged land and preventing pollution as the starting point for land back. The first step to land back is ending the environmental racism of the TBPP’s pollution directed downstream and downwind of FWFN and protecting ancestral land against logging, mining, and other extractive industries. Full article

Coal-fired boilers, including coal-fired power plants (CFPPs) and coal-fired industrial boilers (CFIBs), are an important area for achieving sustainability globally as they are one of the globally important sources of anthropogenic emissions of heavy metals (HMs) due to huge amount of coal consumption. To date, the investigation of atmospheric emission characteristics, speciation, and potential environmental risks of HMs from coal-fired boilers has received widespread attention and achieved significant progress. To characterise the emissions of HMs from coal-fired boilers, research is currently being carried out in the areas of (1) studying the release of HMs from coal combustion processes, (2) developing emission factors and emission inventories, and (3) revealing the cross-media partitioning of HMs between different output streams. Research on the chemical forms of HMs in waste from coal-fired boiler is currently focused on chemical valence and speciation components. The sequential chemical extraction method is currently the most widely used method for investigating the chemical fractionations of HMs in wastes from coal-fired boilers. Studies indicate that different HM elements display differentiated characteristics of speciation in waste from coal-fired boilers. Early studies on potential environmental risk and ecological risk caused by HMs are usually based on actual monitoring values of HMs in the target environmental media. The risk assessment code method and the leaching toxicity method are the most widely used method to study the potential environmental risk of HMs in waste from coal-fired boilers. With the implementation of global carbon emission reduction strategies, the scale of coal-fired boilers and air pollution control technologies are bound to change in the future. Therefore, as an important component of global efforts to achieve sustainable development, more research is needed in the future to improve the accuracy of emission inventories, reveal the mechanisms of HM chemical transformation, and establish methods for potential environmental risk assessment at regional scales. Full article

Low-level lead exposure in children is a major public health issue. Higher-resolution spatial targeting would significantly improve county and state-wide policies and programs for lead exposure prevention that generally intervene across large geographic areas. We use stack-ensemble machine learning, including an elastic net generalized linear model, gradient-boosted machine, and deep neural network, to predict the number of children with venous blood lead levels (BLLs) ≥2 to <5 µg/dL and ≥5 µg/dL in ~1 km² raster cells in the metro Atlanta region using a sample of 92,792 children ≤5 years old screened between 2010 and 2018. Permutation-based predictor importance and partial dependence plots were used for interpretation. Maps of predicted vs. observed values were generated to compare model performance. According to the EPA Toxic Release Inventory for air-based toxic release facility density, the percentage of the population below the poverty threshold, crime, and road network density was positively associated with the number of children with low-level lead exposure, whereas the percentage of the white population was inversely associated. While predictions generally matched observed values, cells with high counts of lead exposure were underestimated. High-resolution geographic prediction of lead-exposed children using ensemble machine learning is a promising approach to enhance lead prevention efforts. Full article

To curb greenhouse gas emissions and reduce atmospheric pollutants in Canada, many pieces of environment legislation are targeted at reducing industrial emissions. Traditional regulation prescribes penalties through fines to discourage industries from polluting, but, in the past two decades, alternative forms of environmental regulation, such as the National Pollutant Release Inventory (NPRI), have been introduced. NPRI is an information management tool which requires industries to self-report emissions data based on a set of guidelines determined by Environment and Climate Change Canada, a federal agency. The tool works to inform the public regarding industry emissions and provides a database that can be analyzed by researchers and regulators to inform emissions trends in Canada. These tools have been successful in other jurisdictions (e.g., United States and Australia). However, research assessing the U.S. Toxic Release Inventory suggests there are fundamental weaknesses in the self-reported nature of the data and incidences of under-reporting. This preliminary study aimed to explore NPRI in Canada and test its effectiveness against the National Air Pollutant Surveillance Network (NAPS), an air quality monitoring program administered by the federal government. While instances of under-reporting were undetected, this study identified areas of weakness in the NPRI tool and instances of increasing emissions across various industrial sectors in Canada. Full article

The U.S. Environmental Protection Agency (USEPA) provides databases that agglomerate data provided by companies or states reporting emissions, releases, wastes generated, and other activities to meet statutory requirements. These databases, often referred to as inventories, can be used for a wide variety of environmental reporting and modeling purposes to characterize conditions in the United States. Yet, users are often challenged to find, retrieve, and interpret these data due to the unique schemes employed for data management, which could result in erroneous estimations or double-counting of emissions. To address these challenges, a system called Standardized Emission and Waste Inventories (StEWI) has been created. The system consists of four python modules that provide rapid access to USEPA inventory data in standard formats and permit filtering and combination of these inventory data. When accessed through StEWI, reported emissions of carbon dioxide to air and ammonia to water are reduced approximately two- and four-fold, respectively, to avoid duplicate reporting. StEWI will greatly facilitate the use of USEPA inventory data in chemical release and exposure modeling and life cycle assessment tools, among other things. To date, StEWI has been used to build the recent USEEIO model and the baseline electricity life cycle inventory database for the Federal LCA Commons. Full article

Disproportionate distribution of air pollution is a major burden on the health of people living in proximity to toxic facilities. There are over 1000 Toxics Release Inventory (TRI) facilities distributed across the state of Illinois. This study investigates and spatially analyzes the relationship between chronic obstructive pulmonary disease (COPD) hospitalizations and toxic emissions from TRI facilities. In addition, this study investigates the connection between COPD hospitalizations and socioeconomic variables. Accounting for dispersion of air pollution beyond the TRI facilities source was attained using the inverse distance weighting interpolation approach. Multiple statistical methods were used including principal components analysis, linear regression, and bivariate local indicators of spatial association (BiLISA). The results from the linear regression model and BiLISA clustering maps show there is a strong connection between COPD hospitalizations and socioeconomic status along with race. TRI emissions were not statistically significant, but there are three major clusters of high COPD hospitalizations with high TRI emissions. Rural areas also seem to carry a higher burden of pollution-emitting facilities and respiratory hospitalizations. Full article

This paper provides a comprehensive review of 71 previous studies on the life cycle assessment (LCA) of nanomaterials (NMs) from 2001 to 2020 (19 years). Although various studies have been carried out to assess the efficiency and potential of wastes for nanotechnology, little attention has been paid to conducting a comprehensive analysis related to the environmental performance and hotspot of NMs, based on LCA methodology. Therefore, this paper highlights and discusses LCA methodology’s basis (goal and scope definition, system boundary, life cycle inventory, life cycle impact assessment, and interpretation) to insights into current practices, limitations, progress, and challenges of LCA application NMs. We found that there is still a lack of comprehensive LCA study on the environmental impacts of NMs until end-of-life stages, thereby potentially supporting misleading conclusions, in most of the previous studies reviewed. For a comprehensive evaluation of LCA of NMs, we recommend that future studies should: (1) report more detailed and transparent LCI data within NMs LCA studies; (2) consider the environmental impacts and potential risks of NMs within their whole life cycle; (3) adopt a transparent and prudent characterization model; and (4) include toxicity, uncertainty, and sensitivity assessments to analyze the exposure pathways of NMs further. Future recommendations towards improvement and harmonization of methodological for future research directions were discussed and provided. This study’s findings redound to future research in the field of LCA NMs specifically, considering that the release of NMs into the environment is yet to be explored due to limited understanding of the mechanisms and pathways involved. Full article

A significant amount of research has been conducted on the impacts of emissions reduction, absorptive capacity, and buffer inventory on firm performance. According to the resource-based view (RBV), absorptive capacity and buffer inventory are organizational capabilities and resources to create sustainable competitive advantages. Yet, the resource orchestration perspective (ROP) of the RBV emphasizes that firms need to develop a new capability to orchestrate and deploy their existing capabilities and resources. From an organizational learning perspective, firms with the low-level release of toxic chemicals have established a structured system and systematic organizational routines, strengthening their learning capabilities to share and use internal and external information across functional areas for continuous improvements. This study explores and seeks to understand toxic emissions through systematic operational routines as an organizational mechanism. These routines orchestrate and deploy the firm-specific absorptive capacity and buffer inventory to generate a sustainable competitive advantage. We examine the impacts of the absorptive capacity and buffer inventory on firm value in terms of Tobin’s Q, respectively. We also explore how such impacts are moderated by toxic emissions. Our results show that the absorptive capacity significantly enhances the market value of firms. However, the relationship between the buffer inventory and firm value is insignificant. Our additional analyses indicate that the impacts of the absorptive capacity and buffer inventory on the firm value are both significantly positive when firms release low toxic chemicals. Our results further suggest that firms can maximize their market value with a high absorptive capacity, high buffer inventory, and low toxic emissions. Full article

Industrial chemicals differ in their treatment methods and types, depending on their physicochemical properties. Highly volatile chemicals are emitted despite installation of preventive facilities, such as scrubbers and adsorption towers. Some countries release a Toxic Release Inventory (TRI), which is a mandatory report on the amount of chemicals emitted annually. This report is released to the citizens to ensure their right to knowledge and life. Numerous methods have been devised to investigate the amount of chemical emissions. There are four methods to estimate TRI emissions (Emission Factor Method; Material Balance Method; Source Testing Method; Emission Model Method). Moreover, efforts have been made to increase awareness and formulate plans to reduce chemical emissions. Despite this, the TRI method tends to underestimate and overestimate, especially due to volatile compounds. If the results of the TRI emissions are underestimated, toxic chemicals can have a negative impact on citizens. Volatile compounds are commonly used in chemical manufacturing plants, such as paint plants. In this study, a suitable method for each industrial process was suggested based on conservative estimates of multiple toxic chemical inventory method, focusing on the paint manufacturing process. In the paint manufacturing plant, storage, weighing, and mixing processes should be used emission model method to estimate TRI. In the reaction process, TRI must be estimated by the source test method. In the transfer process, the emission factor method should be used to estimate TRI. In the atmosphere prevention process, the emission factor method or source testing method should be used depending on the physical and chemical properties such as vapor pressure of the chemical. Full article

This paper presents a spatial analysis of the association between industrial benzene emissions and the 10-year incidence rates of cancers likely to be associated with benzene exposure (Lymphohematopoietic, lung and lip cancers) at the county level in Texas. The spatial distribution of incident cases of the above cancers between 2004 and 2013 was assessed at the county level and found to have positive spatial auto-correlation. Subsequently, point pattern analysis was performed on industrial emissions of benzene reported to the Toxic Release Inventory (TRI), revealing a non-random spatial pattern. Universal kriging was performed using the industrial emissions data to derive estimates of ambient benzene levels at the county level. An ordinary linear regression model was fitted using the incidence rates as the outcome and the estimated benzene level along with chosen covariates and the residuals were assessed for lingering spatial auto-correlation. As the residuals showed that spatial auto-correlation persists, a spatial conditional auto-regression (CAR) model was fitted instead. In the spatial CAR linear regression model, estimated levels of ambient benzene were not found to be significantly associated with the 10-year incidence rates of lymphohematopoietic, lung and lip cancers at the county level. Full article

Metallic elements present in livestock manure as co-contaminants have the potential to cause terrestrial ecotoxic impacts when the manure is used as fertilizer on agricultural soils. The magnitude of this impact at country scale in Europe has, to date, not been quantified. Here, we address this knowledge gap by combining recently developed national emission inventories of Cd, Cu, Ni, Pb and Zn releases from manure with metal- and soil-specific comparative toxicity potentials (CTP) calculated for cropland grid cells at 1 × 1 km resolution for 33 European countries. The CTPs account for speciation in environmental fate, exposure and effects, including reduction in the solid-phase reactivity of a metal when it is associated with organic carbon present in the manure. Given the scarcity of inventory data at sub-national level, it was assumed that each unit area of cropland within a given country has the same probability to receive manure. The resulting CTPs span a range of several orders of magnitude reflecting the influence of soil type and properties on the speciation patterns and resulting CTP values. However, when combined with the use of manure in each European country, the resulting national impact scores were mainly explained by the total mass input of metal released to soil rather than by geographic variability in the CTP values. Simple linear regression is then sufficient to predict terrestrial ecotoxic impacts from input mass. Although some changes in ranking of metals and countries were observed, both mass- and impact-based comparisons between metals agreed that Zn and Cu are dominant contributors to total impacts, and that top contributing countries were those emitting the largest amounts of metals. Our findings show that spatially differentiated impact assessment is important for ranking of countries when differences in national emission inventories between countries are smaller than a factor of two (Ni), a factor of three (Cd, Cu, Zn) or a factor of four (Pb). In other cases, ranking of countries can be based on national emission inventories. Full article

The demand for clean energy is strong, and the shift from fossil-fuel-based energy to environmentally friendly sources is the next step to eradicating the world’s greenhouse gas (GHG) emissions. Solar energy technology has been touted as one of the most promising sources for low-carbon, non-fossil fuel energy production. However, the true potential of solar-based technologies is established by augmenting efficiency through satisfactory environmental performance in relation to other renewable energy systems. This paper presents an environmental life-cycle assessment (LCA) of a solar-photovoltaic (PV) system and a solar-thermal system. Single crystalline Si solar cells are considered for the solar PV system and an evacuated glass tube collector is considered for the solar thermal system in this analysis. A life-cycle inventory (LCI) is developed considering all inputs and outputs to assess and compare the environmental impacts of both systems for 16 impact indicators. LCA has been performed by the International Reference Life Cycle Data System (ILCD), Impact 2002+, Cumulative Energy Demand (CED), Eco-points 97, Eco-indicator 99 and Intergovernmental Panel on Climate Change (IPCC) methods, using SimaPro software. The outcomes reveal that a solar-thermal framework provides more than four times release to air ( $100\%$ ) than the solar-PV ( $23.26\%$ ), and the outputs by a solar-PV system to soil ( $27.48\%$ ) and solid waste ( $35.15\%$ ) are about one third that of solar-thermal. The findings also depict that the solar panels are responsible for the most impact in the considered systems. Moreover, uncertainty and sensitivity analysis has also been carried out for both frameworks, which reveal that Li-ion batteries and copper-indium-selenium (CIS)-solar collectors perform better than others for most of the considered impact categories. This study revealed that a superior environmental performance can be achieved by both systems through careful selection of the components, taking into account the toxicity aspects, and by minimizing the impacts related to the solar panel, battery and heat storage. Full article

Ovarian cancer is the fifth leading cause of female cancer mortality in the U.S. and accounts for five percent of all cancer deaths among women. No environmental risk factors for ovarian cancer have been confirmed. We previously reported that ovarian cancer incidence rates at the state level were significantly correlated with the extent of pulp and paper manufacturing. We evaluated that association using county-level data and advanced geospatial methods. Specifically, we investigated the relationship of spatial patterns of ovarian cancer incidence rates with toxic emissions from pulp and paper facilities using data from the Environmental Protection Agency’s Toxic Release Inventory (TRI). Geospatial analysis identified clusters of counties with high ovarian cancer incidence rates in south-central Iowa, Wisconsin, New York, Pennsylvania, Alabama, and Georgia. A bivariate local indicator of spatial autocorrelation (LISA) analysis confirmed that counties with high ovarian cancer rates were associated with counties with large numbers of pulp and paper mills. Regression analysis of state level data indicated a positive correlation between ovarian cancer and water pollutant emissions. A similar relationship was identified from the analysis of county-level data. These data support a possible role of water-borne pollutants from pulp and paper mills in the etiology of ovarian cancer. Full article

Congenital heart disease (CHD) is a serious anomaly for which the etiology remains elusive. We explored temporal trend associations between industrial developmental toxicant (DT) air emissions and CHD in Alberta. Patients born between 2004–2011 with a diagnosis of CHD and 18 DTs from the National Pollutant Release Inventory (2003–2010) were identified. We applied principal component analysis (PCA) to DT amounts and toxicity risk scores (RS) and defined yearly crude CHD and septal defects rates for urban and rural regions. Correlations between DT groups and CHD rates were examined with Spearman test and Bonferroni correction was conducted for multiple comparisons. PCA identified three DT groups: Group 1 (volatile organic compounds (VOCs) and other gases,) Group 2 (other VOCs), and Group 3 (mainly heavy metals). Province-wide, we found associations between Group 1 DTs and CHD and septal defect rates, when using amounts (r = 0.86, CI 0.39, 0.97 and r = 0.89, CI 0.48, 0.98, respectively) and RS (r = 0.88, CI 0.47, 0.98 and r = 0.85, CI 0.36, 0.97, respectively). Rural Group 2 DTs were positively associated with septal defect rates in both amounts released and RS (r = 0.91, CI 0.55, 0.98 and r = 0.91, CI 0.55, 0.98, respectively). In this exploratory study, we found a temporal decrease in emissions and CHD rates in rural regions and a potential positive association between CHD and septal defect rates and mixtures of organic compounds with or without gases. Full article