Accounting for carbon stocks in models of land-use change: an application to Southern Yucatan

To assess the impact of land-use change on carbon stocks, we apply a new methodology, linking ecological and economic modeling, to southern Yucatan, Mexico. A spatial econometric multinomial logit model of ten land-cover classes is estimated (four primary forest categories, three secondary growth categories, an invasive species, and two agricultural land-cover categories), using satellite data on land cover, linked with census socioeconomic data and other biophysical spatial data from 2000. The analysis is novel in that it is the first attempt to link detailed satellite data on land use, with on-the-ground estimates of carbon stocks in a spatial econometric model of land use. The estimated multinomial logit model is then used with two scenarios of future economic growth (“low growth” and “high growth” changes in population, agricultural land use, market access, and education levels) in the region to predict land-cover changes resulting from the economic growth. The per hectare carbon (C) stocks in each land-cover class are derived from previously published estimates of biomass from field sampling across the study region. We consider aboveground-only, aboveground plus soil, transient and non-transient pools of carbon. These estimates are scaled up to the total area in each class according to the predictions of the model baseline and the two development scenarios. Subsequently, the changes in carbon stocks resulting from the predicted land-cover changes are calculated. Under the low growth scenario, carbon stocks declined by 5%; under the high growth scenario, losses were 12%. Including soil C, the proportional losses were lower, but the absolute amount lost was more than double (to 6 Tg C under the low and almost 15 Tg C under the high-growth scenario). This methodology could be further developed for applications in global change policy, such as payments for environmental services (PES) or reduction in emissions from deforestation and degradation (REDD).     

Influence of Small Dams on Downstream Channel Characteristics in Pennsylvania and Maryland: Implications for the Long‐Term Geomorphic Effects of Dam Removal1

Abstract: We evaluate the effects of small dams (11 of 15 sites less than 4 m high) on downstream channels at 15 sites in Maryland and Pennsylvania by using a reach upstream of the reservoir at each site to represent the downstream reach before dam construction. A semi‐quantitative geomorphic characterization demonstrates that upstream reaches occupy similar geomorphic settings as downstream reaches. Survey data indicate that dams have had no measurable influence on the water surface slope, width, and the percentages of exposed bedrock or boulders on the streambed. The median grain diameter (D₅₀) is increased slightly by dam construction, but D₅₀ remains within the pebble size class. The percentage of sand and silt and clay on the bed averages about 35% before dam construction, but typically decreases to around 20% after dam construction. The presence of the dam has therefore only influenced the fraction of finer‐grained sediment on the bed, and has not caused other measurable changes in fluvial morphology. The absence of measurable geomorphic change from dam impacts is explicable given the extent of geologic control at these study sites. We speculate that potential changes that could have been induced by dam construction have been resisted by inerodible bedrock, relatively immobile boulders, well‐vegetated and cohesive banks, and low rates of bed material supply and transport. If the dams of our study are removed, we argue that long‐term changes (those that remain after a period of transient adjustment) will be limited to increases in the percentage of sand and silt and clay on the bed. Thus, dam removal in streams similar to those of our study area should not result in significant long‐term geomorphic changes.     

Biodegradation of disodium cocoamphodiacetate by a wastewater microbial consortium.

Biodegradation of an amphoteric surfactant commonly used in personal care products, disodium cocoamphodiacetate (DSCADA), was evaluated. Results from respirometry experiments indicated that high levels of DSCADA (>216 mg/L) may be toxic to bacteria in wastewater treatment processes. Limited biodegradation, with 50% dissolved organic carbon (DOC) removal and 80% chemical oxygen demand removal was observed in batch assays, while complete removal of the parent compound, DSCADA, was noted. Oxygen biosensors were used to evaluate biodegradability of the metabolites present in the batch samples. Additional aerobic microbial activity was not detected in these samples, even with a residual DOC of approximately 45 mg/L. Results from this research indicate that biodegradability of DSCADA is limited and recalcitrant metabolites may be formed. Because DSCADA is a commonly used surfactant and is present in domestic and industrial wastewater, the associated risk posed by residual compounds should be carefully evaluated.     

Effect of Matrix–Particle Interfacial Adhesion on the Mechanical Properties of Poly(lactic acid)/Wood-Flour Micro-Composites

The influence of interfacial matrix/particle adhesion on the mechanical properties of poly(lactic acid) (PLA) micro-composites was investigated. The tensile strength of PLA/wood-flour micro-composites is almost independent of wood-flour content, suggesting only weak adhesion exists between the PLA matrix and the wood-flour particles. The addition of wood-flour resulted in an increase of up to 95% in the tensile modulus, in comparison with pure PLA, which showed a more resilient matrix. The addition of a coupling agent, methylenediphenyl-diisocyanate (MDI) to the composition resulted in an increase in tensile strength and tensile modulus of the micro-composites, of 10 and 135%, respectively, indicating enhanced matrix–particle interfacial adhesion. SEM and electron probe microanalysis provided evidence of improved interfacial adhesion between PLA and wood-flour particles from the addition of MDI. In contrast, addition of PEAA resulted in a micro-composite displaying substantially reduced tensile strength, up to 35% and a slightly increased in impact strength, up to 15%, consistent with the introduction of the rubbery PEAA component into the polymeric matrix. No evidence for increased matrix–particle adhesion was found for the PLA/wood-flour micro-composites containing PEAA.     

Assigning concentration values for dioxin and furan congeners in human serum when measurements are below limits of detection: an observational approach

Concentrations of polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) in dietary sources for humans have been declining over the previous two decades. These declines have been accompanied by decreases in concentrations of these compounds in humans, as evidenced by measurements in blood and milk. Because of the decreasing concentrations of PCDD/PCDFs in the environment and in humans, measuring PCDD/PCDF congeners in humans has become increasingly difficult, despite advances in analytic methods. An observational approach was recently described to address the quandary of non-detectable results in determining toxic equivalents. This approach, called the congener ratio approach, is specifically for cases where concentrations of 2,3,7,8-TCDD (TCDD) are below the limit of detection (LOD), and where concentrations of 1,2,3,7,8-pentachlorodibenzo-p-dioxin (PeCDD) are equal to or above the LOD. Development of this approach relied on evaluating data on measured concentrations of TCDD and PeCDD in human serum from the general population. The congener ratio approach for TCDD and PeCDD was based on the concentration of TCDD being approximately 40% that of PeCDD in serum from the general population. Additional analyses presented here reveal that when concentrations of both congeners are above the LOD, the data appear to generally support the congener ratio approach for TCDD and PeCDD, with the caveat that gender may affect the ratio. However, the TCDD/PeCDD relation is less clear when TCDD is less than the LOD; in this situation, the relation overpredicts levels of TCDD approximately 80% of the time for the 2001-2002 NHANES database. Using the congener ratio approach for other PCDD/PCDF congeners requires assessing the correlation and the frequency of detection for both TCDD and PeCDD.     

Calculation of serum "total lipid" concentrations for the adjustment of persistent organohalogen toxicant measurements in human samples

Persistent organohalogen toxicants such as 2,3,7,8-tetrachlorodibenzo-p-dioxin or polychlorinated biphenyls measured in human serum are often expressed on a lipid weight basis, most commonly by dividing the toxicants' concentration by the weight of total lipids in the sample. Therefore, the manner in which this lipid adjustment is calculated may influence the final reported result. Gravimetric total lipid assays have been used, but they are time-consuming and sometimes may be ill-defined. Consequently, alternative methods using enzymatic assays have been developed based on summing the individual lipid species measured. Recent reports, however, have suggested that significantly different total lipid results may be obtained when using alternative formulae in a summation approach. In this report, we summarize the results obtained from lipid measurements of nearly 900 samples made as part of a study of a group of older American men (mean age 62 years), and we compare our total lipid estimates obtained by using both our standard and "short" formula (the latter based on total cholesterol and triglycerides only) with results obtained using the recently proposed alternative formulae. Our findings indicate that both our long and short formulae provide similar estimates of serum total lipid concentrations, and that differences observed in lipid estimates when using the newer alternative summation methods may reflect differences in how the term "total lipid" is defined, especially with regard to the need to include the contribution of the weight of the cholesterol ester fatty acids in the calculation.     

Quantifying sample biases of inland lake sampling programs in relation to lake surface area and land use/cover

We quantified potential biases associated with lakes monitored using non-probability based sampling by six state agencies in the USA (Michigan, Wisconsin, Iowa, Ohio, Maine, and New Hampshire). To identify biases, we compared state-monitored lakes to a census population of lakes derived from the National Hydrography Dataset. We then estimated the probability of lakes being sampled using generalized linear mixed models. Our two research questions were: (1) are there systematic differences in lake area and land use/land cover (LULC) surrounding lakes monitored by state agencies when compared to the entire population of lakes? and (2) after controlling for the effects of lake size, does the probability of sampling vary depending on the surrounding LULC features? We examined the biases associated with surrounding LULC because of the established links between LULC and lake water quality. For all states, we found that larger lakes had a higher probability of being sampled compared to smaller lakes. Significant interactions between lake size and LULC prohibit us from drawing conclusions about the main effects of LULC; however, in general lakes that are most likely to be sampled have either high urban use, high agricultural use, high forest cover, or low wetland cover. Our analyses support the assertion that data derived from non-probability-based surveys must be used with caution when attempting to make generalizations to the entire population of interest, and that probability-based surveys are needed to ensure unbiased, accurate estimates of lake status and trends at regional to national scales.     

Using a relative health indicator (RHI) metric to estimate health risk reductions in drinking water

When a new drinking water regulation is being developed, the USEPA conducts a health risk reduction and cost analysis to, in part, estimate quantifiable and non-quantifiable cost and benefits of the various regulatory alternatives. Numerous methodologies are available for cumulative risk assessment ranging from primarily qualitative to primarily quantitative. This research developed a summary metric of relative cumulative health impacts resulting from drinking water, the relative health indicator (RHI). An intermediate level of quantification and modeling was chosen, one which retains the concept of an aggregated metric of public health impact and hence allows for comparisons to be made across “cups of water,” but avoids the need for development and use of complex models that are beyond the existing state of the science. Using the USEPA Six-Year Review data and available national occurrence surveys of drinking water contaminants, the metric is used to test risk reduction as it pertains to the implementation of the arsenic and uranium maximum contaminant levels and quantify “meaningful” risk reduction. Uranium represented the threshold risk reduction against which national non-compliance risk reduction was compared for arsenic, nitrate, and radium. Arsenic non-compliance is most significant and efforts focused on bringing those non-compliant utilities into compliance with the 10 μg/L maximum contaminant level would meet the threshold for meaningful risk reduction.