Environmental management intentions: An empirical investigation of Argentina's polluting firms

This paper builds on past behavioural research which explicitly recognises that ‘actions’ are preceded by ‘intentions’ which are in turn determined by individual mindsets, locus of control, principles of governances and context factors. More concretely, it presents a model that investigates the extent to which environmental behavioural intentions are explained by i) managers' core values, basic assumptions, and beliefs, ii) individual and socio-cognitive frames, iii) principles of governance, and iv) context factors. Context factors include obstacles and drivers of greener behaviours, market pressures, and firm demographics. The resulting theoretical framework is tested empirically through regression analyses that use data gathered from a survey of 536 Argentinean firms in polluting industries. The model performs well, explaining approximately 50% of the variations in the (pro) environmental behaviour of firms. Policy implications are briefly discussed.     

Mental health outcomes of job stress among Chinese teachers: role of stress resource factors and burnout

This study examined the mental health outcomes of job stress among Chinese teachers in Hong Kong. A total of 269 Chinese teachers participated in Study 1 which provided cross‐sectional data regarding the associations among stress resource factors, burnout, and negative mental health. Study 2 was a six‐month longitudinal study which aimed to establish the direction of the associations among the hypothesized variables across two time points with a separate sample of 61 Chinese secondary school teachers. Results of the structural equation modelling analyses on the cross‐sectional data at T1 showed that stress resource factors of self‐efficacy and proactive attitude were negatively related to burnout, which in turn had a direct effect on negative mental health. Stress resource factors were also directly linked to mental health status of teachers. Results of similar analyses on the longitudinal data at T2 further indicated that burnout at T1 had a direct impact on burnout at T2, which in turn had a direct effect on negative mental health at T2. Findings and limitations of the study were discussed. Copyright © 2001 John Wiley & Sons, Ltd.     

Potential allelopathic effect of Pinus halepensis in the secondary succession: an experimental approach

Summary. Recent economic and social changes in north Mediterranean regions have led to an important rural depopulation. Consequently, meadows developed on abandoned agricultural lands (characterized by high species richness) undergo reforestation. These former fields are mainly colonized by Pinus halepensis Miller, which is known to synthetize a wide range of secondary metabolites, among these, some could influence plant succession through allelopathy. The allelopathic potential of P. halepensis, was tested against two target species (Lactuca sativa L. and Linum strictum L.) with aqueous extracts obtained from different organs (root and needle) taking into account the individual age (±10, ±30 and > 60 years old). Root and needle extracts affected differently germination and growth of the two target species, the responses varying with concentration of extracts, age and organs tested. The strongest inhibitory effect was observed on the germination and growth of L. strictum, exposed to needle extracts of young P. halepensis (±10 years old), and root extracts of older P. halepensis (> 30 years old). These extracts contained several phenolic acids (e.g. 4-hydroxybenzoic acid and p-coumaric acid), which are known as allelochemicals and their concentrations vary with age and organ tested. Hence, P. halepensis could influence secondary succession through the release of potential allelochemicals in the environment by leaf leachates or root exudates.     

Particulate matter speciation profiles for light-duty gasoline vehicles in the United States

Representative profiles for particulate matter particles less than or equal to 2.5 µm (PM_2.5) are developed from the Kansas City Light-Duty Vehicle Emissions Study for use in the U.S. Environmental Protection Agency (EPA) vehicle emission model, the Motor Vehicle Emission Simulator (MOVES), and for inclusion in the EPA SPECIATE database for speciation profiles. The profiles are compatible with the inputs of current photochemical air quality models, including the Community Multiscale Air Quality Aerosol Module Version 6 (AE6). The composition of light-duty gasoline PM_2.5 emissions differs significantly between cold start and hot stabilized running emissions, and between older and newer vehicles, reflecting both impacts of aging/deterioration and changes in vehicle technology. Fleet-average PM_2.5 profiles are estimated for cold start and hot stabilized running emission processes. Fleet-average profiles are calculated to include emissions from deteriorated high-emitting vehicles that are expected to continue to contribute disproportionately to the fleet-wide PM_2.5 emissions into the future. The profiles are calculated using a weighted average of the PM_2.5 composition according to the contribution of PM_2.5 emissions from each class of vehicles in the on-road gasoline fleet in the Kansas City Metropolitan Statistical Area. The paper introduces methods to exclude insignificant measurements, correct for organic carbon positive artifact, and control for contamination from the testing infrastructure in developing speciation profiles. The uncertainty of the PM_2.5 species fraction in each profile is quantified using sampling survey analysis methods. The primary use of the profiles is to develop PM_2.5 emissions inventories for the United States, but the profiles may also be used in source apportionment, atmospheric modeling, and exposure assessment, and as a basis for light-duty gasoline emission profiles for countries with limited data.

Implications: PM_2.5 speciation profiles were developed from a large sample of light-duty gasoline vehicles tested in the Kansas City area. Separate PM_2.5 profiles represent cold start and hot stabilized running emission processes to distinguish important differences in chemical composition. Statistical analysis was used to construct profiles that represent PM_2.5 emissions from the U.S. vehicle fleet based on vehicles tested from the 2005 calendar year Kansas City metropolitan area. The profiles have been incorporated into the EPA MOVES emissions model, as well as the EPA SPECIATE database, to improve emission inventories and provide the PM_2.5 chemical characterization needed by CMAQv5.0 for atmospheric chemistry modeling.     

Do Nutrients Limit Algal Periphyton in Small Blackwater Coastal Plain Streams?1

Abstract: We examine the potential for nutrient limitation of algal periphyton biomass in blackwater streams draining the Georgia coastal plain. Previous studies have investigated nutrient limitation of planktonic algae in large blackwater rivers, but virtually no scientific information exists regarding how algal periphyton respond to nutrients under different light conditions in smaller, low‐flow streams. We used a modification of the Matlock periphytometer (nutrient‐diffusing substrata) to determine if algal growth was nutrient limited and/or light limited at nine sites spanning a range of human impacts from relatively undisturbed forested basins to highly disturbed agricultural sites. We employed four treatments in both shaded and sunny conditions at each site: (1) control, (2) N (NO₃‐N), (3) P (PO₄‐P), and (4) N + P (NO₃‐N + PO₄‐P). Chlorophyll a response was measured on 10 replicate substrates per treatment, after 15 days of in situ exposure. Chlorophyll a values did not approach what have been defined as nuisance levels (i.e., 100‐200 mg/m²), even in response to nutrient enrichment in sunny conditions. For Georgia coastal plain streams, algal periphyton growth appears to be primarily light limited and can be secondarily nutrient limited (most commonly by P or N + P combined) in light gaps and/or open areas receiving sunlight.     

Characterizing perfluorooctanoate in ambient air near the fence line of a manufacturing facility: comparing modeled and monitored values

In order to improve our understanding of the nature, measurement and prediction of salts of perfluorooctanoic acid (PFOA) in air, two studies were performed along the fence line of a fluoropolymer manufacturing facility. First, a six-event, 24-hr monitoring series was performed around the fence line using the OSHA versatile sampler (OVS) system. Perfluorooctanoate concentrations were determined as perfluorooctanoic acid (PFOA) via liquid chromatography and mass spectrometry. Those data indicated that the majority of the PFOA was present as a particulate. No vapor-phase PFOA was detected above a detection limit of approximately 0.07 microg/m3. A follow-up study using a high-volume cascade impactor verified the range of concentrations observed in the OVS data. Both studies aligned with the major transport direction and range of concentrations predicted by an air dispersion model, demonstrating that model predictions agreed with monitoring results. Results from both monitoring methods and predictions from air dispersion modeling showed the primary direction of transport for PFOA was in the prevailing wind direction. The PFOA concentration measured at the site fence over the 10-week sampling period ranged from 0.12 to 0.9 microg/m3. Modeled predictions for the same time period ranged from 0.12 to 3.84 microg/m3. Less than 6% of the particles were larger than 4 microm in size, while almost 60% of the particles were below 0.3 microm. These studies are believed to be the first published ambient air data for PFOA in the environment surrounding a manufacturing facility.