Relationships between value orientations, self-determined motivational types and pro-environmental behavioural intentions

We examined the predictive power of egoistic, altruistic and biospheric value orientations and six types of self-determined motivations (i.e. intrinsic motivation, integrated regulation, identified regulation, introjected regulation, external regulation, and amotivation) toward acting pro-environmentally for explaining two types of pro-environmental intentions in two questionnaire studies among student samples (N = 304 and N = 520). The two pro-environmental intentional measures included choosing a car based on environmental performance and donating to an environmental organisation. Values were more predictive of pro-environmental intentions than were self-determined motivational types, although these differences were not always statistically significant. Furthermore, we explored how value orientations are related to self-determined motivational types. The more respondents were altruistically and biospherically oriented, the more they were self-determined to act pro-environmentally. When respondents endorsed egoistic values, they were less self-determined towards acting in a pro-environmental way. When altruistic and especially biospheric values were important predictors of pro-environmental intentions, stronger types of self-determined motivations were also important to explain intentions. And, when egoistic values contributed uniquely to the explanation of pro-environmental intentions, amotivation and external regulation (i.e. less self-determined motivational types) were most relevant for explaining intentions.     

Dilution-based emissions sampling from stationary sources: Part 1--Compact sampler methodology and performance

This paper presents the design and performance of a compact dilution sampler (CDS) for characterizing fine particle emissions from stationary sources. The sampler is described, along with the methodology adopted for its use. Dilution sampling has a number of advantages, including source emissions that are measured under conditions simulating stack gas entry and mixing in the ambient atmosphere. This is particularly important for characterizing the semivolatile species in effluents as a part of particulate emissions. The CDS characteristics and performance are given, along with sampling methodology. The CDS was compared with a reference dilution sampler. The results indicate that the two designs are comparable for tests on gas-fired units and a diesel electrical generator. The performance data indicate that lower detection limits can be achieved relative to current regulatory methods for particulate emissions. Test data for the fine particulate matter (PM2.5) emissions are provided for comparison with U.S. Environment Protection Agency (EPA) Conditional Test Method 040 for filterable particulate matter (FPM) and the EPA Method 202 for condensable particulate matter. This comparison showed important differences between methods, depending on whether a comparison is done between in situ FPM determinations or the sum of such values with condensable PM from liquid filled impingers chilled in an ice bath. These differences are interpretable in the light of semivolatile material present in the stack effluent and, in some cases, differences in detection and quantification limits. Determination of emissions from combustors using liquid fuels can be readily achieved using 1-hr sampling with the CDS. Emissions from gasfired combustors are very low, requiring careful attention to sample volumes. Sampling volumes corresponding with 6-hr operation were used for the combined mass and broad chemical speciation. Particular attention to dilution sampler operation with clean dilution air also is essential for gas-fired sources.     

Evaluations of the chemical mass balance method for determining contributions of gasoline and diesel exhaust to ambient carbonaceous aerosols

The US. Department of Energy Gasoline/Diesel PM Split Study was conducted to assess the sources of uncertainties in using an organic compound-based chemical mass balance receptor model to quantify the relative contributions of emissions from gasoline (or spark ignition [SI]) and diesel (or compression ignition [CI]) engines to ambient concentrations of fine particulate matter (PM2.5) in California's South Coast Air Basin (SOCAB). In this study, several groups worked cooperatively on source and ambient sample collection and quality assurance aspects of the study but worked independently to perform chemical analysis and source apportionment. Ambient sampling included daily 24-hr PM2.5 samples at two air quality-monitoring stations, several regional urban locations, and along freeway routes and surface streets with varying proportions of automobile and truck traffic. Diesel exhaust was the dominant source of total carbon (TC) and elemental carbon (EC) at the Azusa and downtown Los Angeles, CA, monitoring sites, but samples from the central part of the air basin showed nearly equal apportionments of CI and SI. CI apportionments to TC were mainly dependent on EC, which was sensitive to the analytical method used. Weekday contributions of CI exhaust were higher for Interagency Monitoring of Protected Visual Environments (IMPROVE; 41+/-3.7%) than Speciation Trends Network (32+/-2.4%). EC had little effect on SI apportionment. SI apportionments were most sensitive to higher molecular weight polycyclic aromatic hydrocarbons (indeno[123-cd]pyrene, benzo(ghi)perylene, and coronene) and several steranes and hopanes, which were associated mainly with high emitters. Apportionments were also sensitive to choice of source profiles. CI contributions varied from 30% to 60% of TC when using individual source profiles rather than the composites used in the final apportionments. The apportionment of SI vehicles varied from 1% to 12% of TC depending on the specific profile that was used. Up to 70% of organic carbon (OC) in the ambient samples collected at the two fixed monitoring sites could not be apportioned to directly emitted PM emissions.     

Metals in sediments and mangrove oysters (Crassostrea rhizophorae) from the Caroni Swamp,Trinidad

Metals can have significant impacts on inhabitants of mangrove swamps as well as consumers of mangrove-associated fauna. Yet, for several Caribbean islands, assessments regarding the impact of metals on such ecosystems are particularly sparse. The present study investigated the distribution and potential impact of Cd, Cr, Cu, Ni, Pb and Zn in the Caroni Swamp, Trinidad and Tobago’s largest mangrove ecosystem. Surface sediments and mangrove oysters (Crassostrea rhizophorae) from 10 sites in the swamp were analysed for the 6 identified metals. The concentration ranges (in μg/g dry wt.) of metals in sediments from Caroni Swamp were: Zn (113.4–264.6), Cr (27–69.7), Ni (10.7–41.1) and Cu (11–40.7). Based on Canadian Sediment Quality Guidelines (CSQGs), metals in sediments posed a low to medium risk to aquatic life. The concentration ranges (in μg/g wet wt.) for metals in Crassostrea rhizophorae tissues were: Zn (123.2–660), Cu (4.2–12.3), Ni (0.1–5.5), Pb (0.1–0.9), Cr (0.2–0.3) and Cd (0.1–0.2). Multiple evaluations indicated that zinc posed a potential threat to the health of oyster consumers. Information from this study is vital for managing the Caroni Swamp, safeguarding the health of consumers of shellfish on this Caribbean island and serving as a useful baseline for future local and regional risk assessments.     

Urban stream syndrome in a small,lightly developed watershed: a statistical analysis of water chemistry parameters,land use patterns,and natural sources

The relationships among land use patterns, geology, soil, and major solute concentrations in stream water for eight tributaries of the Kayaderosseras Creek watershed in Saratoga County, NY, were investigated using Pearson correlation coefficients and multivariate regression analysis. Sub-watersheds corresponding to each sampling site were delineated, and land use patterns were determined for each of the eight sub-watersheds using GIS. Four land use categories (urban development, agriculture, forests, and wetlands) constituted more than 99 % of the land in the sub-watersheds. Eleven water chemistry parameters were highly and positively correlated with each other and urban development. Multivariate regression models indicated urban development was the most powerful predictor for the same eleven parameters (conductivity, TN, TP, NO $_{3}^-$ , Cl^?, HCO $_{3}^-$ , SO $_{4}^{2-}$ , Na⁺, K⁺, Ca²⁺, and Mg²⁺). Adjusted R ² values, ranging from 19 to 91 %, indicated that these models explained an average of 64 % of the variance in these 11 parameters across the samples and 70 % when Mg²⁺ was omitted. The more common R ², ranging from 29 to 92 %, averaged 68 % for these 11 parameters and 72 % when Mg²⁺ was omitted. Water quality improved most with forest coverage in stream watersheds. The strong associations between water quality variables and urban development indicated an urban source for these 11 water quality parameters at all eight sampling sites was likely, suggesting that urban stream syndrome can be detected even on a relatively small scale in a lightly developed area. Possible urban sources of Ca²⁺ and HCO $_{3}^-$ are suggested.     

Trust,but verify: social media models for disaster management

A lack of trust in the information exchanged via social media may significantly hinder decisionmaking by community members and emergency services during disasters. The need for timely information at such times, though, challenges traditional ways of establishing trust. This paper, building on a multi‐year research project that combined social media data analysis and participant observation within an emergency management organisation and in‐depth engagement with stakeholders across the sector, pinpoints and examines assumptions governing trust and trusting relationships in social media disaster management. It assesses three models for using social media in disaster management—information gathering, quasi‐journalistic verification, and crowdsourcing—in relation to the guardianship of trust to highlight the verification process for content and source and to identify the role of power and responsibilities. The conclusions contain important implications for emergency management organisations seeking to enhance their mechanisms for incorporating user‐generated information from social media sources in their disaster response efforts.     

Estimating Contributions of Nitrate and Herbicides From Groundwater to Headwater Streams,Northern Atlantic Coastal Plain,United States1

Abstract: Groundwater transport often complicates understanding of surface‐water contamination. We estimated the regional flux of nitrate and selected herbicides from groundwater to nontidal headwater streams of the Atlantic Coastal Plain (New Jersey through North Carolina) based on late‐winter or spring base‐flow samples from 174 streams. Sampled streams were selected randomly, and flux estimates are based on resulting population estimates rather than on empirical models, which have been used previously for similar estimates. Base‐flow flux in the estimated 8,834 headwater streams of the study area are an estimated 21,200 kg/day of nitrate (as N) and 5.83, 0.565, and 20.7 kg/day of alachlor, atrazine, and metolachlor (and selected degradates), respectively. Base‐flow flux of alachlor and metolachlor is <3% of the total base‐flow flux of those compounds plus degradates. Base‐flow flux of nitrate and herbicides as a percentage of applications is typically highest in well‐drained areas and lowest in areas with abundant poor drainage and anoxic conditions. In Coastal Plain watersheds of Albemarle and Pamlico Sounds, <2% of applied nitrogen reaches headwater streams as base flow. On the Delmarva Peninsula part of the Chesapeake Bay watershed, however, more than 10% of such applications are transported through groundwater to streams, and base‐flow nitrate flux represents 70% of total nitrogen flux in headwater streams.     

Reference conditions for rivers of the German Baltic Sea catchment: reconstructing nutrient regimes using the model MONERIS

We introduce an approach for establishing reference conditions (RC) for rivers of the German Baltic Sea catchment, based on predictive modelling. An extensive data set of statistics from the year 1880 was coupled with literature data, providing a comprehensive basis for the calculation of regional historical nutrient emissions into rivers, river nutrient concentrations, and nutrient loading into the sea. Four different scenarios were calculated: scenario 1 assumed RC following previously established criteria for lakes (Poikane et al. in Environ Manag 45(6):1286–1298, 2010), scenario 4 applied the nutrient emission conditions of 1880 (considering non-intensive land usage, the presence of tile drainage systems, sewer systems, and the human population from 1880), and scenarios 2 and 3 considered intermediate conditions. Our results showed that nutrient emissions from scenario 1 accounted for approximately one-tenth of the currently observed total nitrogen (TN) and total phosphorus (TP) emissions. The nutrient emissions calculated for 1880 (scenario 4) were found to be 47 % (TN) and 55 % (TP) higher than those calculated considering reference lake conditions (scenario 1). Our results suggest that RC nutrient concentrations in rivers in the German Baltic Sea catchment were clearly below 0.05 mg/l for TP and 1 mg/l for TN. This range is in accordance with historical and calculated pristine nutrient concentrations from other rivers in similar catchments.     

Temporal Variations of PM2.5, PM10, and Gaseous Precursors during the 1995 Integrated Monitoring Study in Central California

ABSTRACT

The spatial and temporal distributions of particle mass and its chemical constituents are essential for understanding the source-receptor relationships as well as the chemical, physical, and meteorological processes that result in elevated particulate concentrations in California’s San Joaquin Valley (SJV). Fine particulate matter ₍PM_2.5), coarse particulate matter (PM₁₀), and aerosol precursor gases were sampled on a 3-hr time base at two urban (Bakersfield and Fresno) and two non-urban (Kern Wildlife Refuge and Chowchilla) core sites in the SJV during the winter of 1995–1996.

Day-to-day variations of PM_2.5 and PM₁₀ and their chemical constituents were influenced by the synoptic-scale meteorology and were coherent among the four core sites. Under non-rainy conditions, similar diurnal variations of PM_2.5 and coarse aerosol were found at the two urban sites, with concentrations peaking during the nighttime hours. Conversely, PM_2.5 and coarse aerosol peaked during the morning and afternoon hours at the two non-urban sites. Under rainy and foggy conditions, these diurnal patterns were absent or greatly suppressed.

In the urban areas, elevated concentrations of primary pollutants (e.g., organic and elemental carbons) during the late afternoon and nighttime hours reflected the impact from residential wood combustion and motor vehicle exhaust. During the daytime, these concentrations decreased as the mixed layer deepened. Increases of secondary nitrate and sulfate concentrations were found during the daylight hours as a result of photochemical reactions. At the non-urban sites, the same increases in secondary aerosol concentrations occurred during the daylight hours but with a discernable lag time. Concentrations of the primary pollutants also increased at the non-urban sites during the daytime. These observations are attributed to mixing aloft of primary aerosols and secondary precursor gases in urban areas followed by rapid transport aloft to non-urban areas coupled with photochemical conversion.