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Environmental Science and Pollution Research - Fruits are the valuable and important components of human diet. Among them, Prunus persica is a rich source of different minerals and dietary fibers....  相似文献   
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The present study deals with detailed hydrochemical assessment of groundwater within the Saq aquifer. The Saq aquifer which extends through the NW part of Saudi Arabia is one of the major sources of groundwater supply. Groundwater samples were collected from about 295 groundwater wells and analyzed for various physico-chemical parameters such as electrical conductivity (EC), pH, temperature, total dissolved solids (TDS), Na+, K+, Ca2+, Mg2+, CO3 ?, HCO3 ?, Cl?, SO4 2?, and NO3 ?. Groundwater in the area is slightly alkaline and hard in nature. Electrical conductivity (EC) varies between 284 and 9,902?μS/cm with an average value of 1,599.4 μS/cm. The groundwater is highly mineralized with approximately 30 % of the samples having major ion concentrations above the WHO permissible limits. The NO3 ? concentration varies between 0.4 and 318.2 mg/l. The depth distribution of NO3 ? concentration shows higher concentration at shallow depths with a gradual decrease at deeper depths. As far as drinking water quality criteria are concerned, study shows that about 33 % of samples are unfit for use. A detailed assessment of groundwater quality in relation to agriculture use reveals that 21 % samples are unsuitable for irrigation. Using Piper’s classification, groundwater was classified into five different groups. Majority of the samples show Mix-Cl-SO4- and Na-Cl-types water. The abundances of Ca2+ and Mg2+ over alkalis infer mixed type of groundwater facies and reverse exchange reactions. The groundwater has acquired unique chemical characteristics through prolonged rock-water interactions, percolation of irrigation return water, and reactions at vadose zone.  相似文献   
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The effectiveness of emissions control programs designed to reduce concentrations of airborne particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) in California's San Joaquin Valley was studied in the year 2030 under three growth scenarios: low, medium, and high population density. Base-case inventories for each choice of population density were created using a coupled emissions modeling system that simultaneously considered interactions between land use and transportation, area source, and point source emissions. The ambient PM2.5 response to each combination of population density and emissions control was evaluated using a regional chemical transport model over a 3-week winter stagnation episode. Comparisons between scenarios were based on regional average and population-weighted PM2.5 concentrations. In the absence of any emissions control program, population-weighted concentrations of PM2.5 in the future San Joaquin Valley are lowest under growth scenarios that emphasize low population density. A complete ban on wood burning and a 90% reduction in emissions from food cooking operations and diesel engines must occur before medium- to high-density growth scenarios result in lower population-weighted concentrations of PM2.5. These trends partly reflect the fact that existing downtown urban cores that naturally act as anchor points for new high-density growth in the San Joaquin Valley are located close to major transportation corridors for goods movement. Adding growth buffers around transportation corridors had little impact in the current analysis, since the 8-km resolution of the chemical transport model already provided an artificial buffer around major emissions sources.

Assuming that future emissions controls will greatly reduce or eliminate emissions from residential wood burning, food cooking, and diesel engines, the 2030 growth scenario using “as-planned” (medium) population density achieves the lowest population-weighted average PM2.5 concentration in the future San Joaquin Valley during a severe winter stagnation event.

Implications: The San Joaquin Valley is one of the most heavily polluted air basins in the United States that are projected to experience strong population growth in the coming decades. The best plan to improve air quality in the region combines medium- or high-density population growth with rigorous emissions controls. In the absences of controls, high-density growth leads to increased population exposure to PM2.5 compared with low-density growth scenarios (urban sprawl).  相似文献   
5.
Methods previously published by this laboratory for analyzing thin dust coatings of airborne particulates have been further evaluated, as applied to vast air pollution surveys. It was demonstrated that choice of glass fiber filters adapted to high-volume samplers restricts the analysis to a limited number of elements, such as lead. More flexibility and versatility are attained through the use of organic membrane filters mounted in small plastic monitors which permit multi-elemental analysis at least as accurately as with other popular but time-consuming techniques. These qualities of speed and accuracy allow shorter intervals of sampling which are normally required for better statistical assessment of broad air pollution surveys. Sensitivity of the technique reaches a value close to 0.05 μg/m3, while time of analysis required is about five minutes per element after receipt of the sample.  相似文献   
6.
The effectiveness of emissions control programs designed to reduce concentrations of airborne particulate matter with an aerodynamic diameter < 2.5 microm (PM2.5) in California's San Joaquin Valley was studied in the year 2030 under three growth scenarios: low, medium, and high population density. Base-case inventories for each choice of population density were created using a coupled emissions modeling system that simultaneously considered interactions between land use and transportation, area source, and point source emissions. The ambient PM2.5 response to each combination of population density and emissions control was evaluated using a regional chemical transport model over a 3-week winter stagnation episode. Comparisons between scenarios were based on regional average and population-weighted PM2.5 concentrations. In the absence of any emissions control program, population-weighted concentrations of PM2.5 in the future San Joaquin Valley are lowest undergrowth scenarios that emphasize low population density. A complete ban on wood burning and a 90% reduction in emissions from food cooking operations and diesel engines must occur before medium- to high-density growth scenarios result in lower population-weighted concentrations of PM2.5. These trends partly reflect the fact that existing downtown urban cores that naturally act as anchor points for new high-density growth in the San Joaquin Valley are located close to major transportation corridors for goods movement. Adding growth buffers around transportation corridors had little impact in the current analysis, since the 8-km resolution of the chemical transport model already provided an artificial buffer around major emissions sources. Assuming that future emissions controls will greatly reduce or eliminate emissions from residential wood burning, food cooking, and diesel engines, the 2030 growth scenario using "as-planned" (medium) population density achieves the lowest population-weighted average PM2.5 concentration in the future San Joaquin Valley during a severe winter stagnation event. Implications: The San Joaquin Valley is one of the most heavily polluted air basins in the United States that are projected to experience strong population growth in the coming decades. The best plan to improve air quality in the region combines medium- or high-density population growth with rigorous emissions controls. In the absences of controls, high-density growth leads to increased population exposure to PM2.5 compared with low-density growth scenarios (urban sprawl).  相似文献   
7.
Future air pollution emissions in the year 2030 were estimated for the San Joaquin Valley (SJV) in central California using a combined system of land use, mobile, off-road, stationary, area, and biogenic emissions models. Four scenarios were developed that use different assumptions about the density of development and level of investment in transportation infrastructure to accommodate the expected doubling of the SJV population in the next 20 years. Scenario 1 reflects current land-use patterns and infrastructure while scenario 2 encouraged compact urban footprints including redevelopment of existing urban centers and investments in transit. Scenario 3 allowed sprawling development in the SJV with reduced population density in existing urban centers and construction of all planned freeways. Scenario 4 followed currently adopted land use and transportation plans for the SJV. The air quality resulting from these urban development scenarios was evaluated using meteorology from a winter stagnation event that occurred on December 15th, 2000 to January 7th 2001. Predicted base-case PM2.5 mass concentrations within the region exceeded 35 μg m?3 over the 22-day episode. Compact growth reduced the PM2.5 concentrations by ~1 μg m?3 relative to the base-case over most of the SJV with the exception of increases (~1 μg m?3) in urban centers driven by increased concentrations of elemental carbon (EC) and organic carbon (OC). Low-density development increased the PM2.5 concentrations by 1–4 μg m?3 over most of the region, with decreases (0.5–2 μg m?3) around urban areas. Population-weighted average PM2.5 concentrations were very similar for all development scenarios ranging between 16 and 17.4 μg m?3. Exposure to primary PM components such as EC and OC increased 10–15% for high density development scenarios and decreased by 11–19% for low-density scenarios. Patterns for secondary PM components such as nitrate and ammonium ion were almost exactly reversed, with a 10% increase under low-density development and a 5% decrease under high density development. The increased human exposure to primary pollutants such as EC and OC could be predicted using a simplified analysis of population-weighted primary emissions. Regional planning agencies should develop thresholds of population-weighted primary emissions exposure to guide the development of growth plans. This metric will allow them to actively reduce the potential negative impacts of compact growth while preserving the benefits.  相似文献   
8.

Polymer materials are vulnerable to damages, failures, and degradations, making them economically unreliable. Self-healing polymers, on the other hand, are multifunctional materials with superior properties of autonomic recovery from physical damages. These materials are suitable for biomedical and tissue engineering in terms of cost and durability. Schiff base linkages-based polymer materials are one of the robust techniques owing to their simple self-healing mechanism. These are dynamic reversible covalent bonds, easy to fabricate at mild conditions, and can self-reintegrate after network disruption at physiological conditions making them distinguished. Here we review self-healing polymer materials based on Schiff base bonds. We discuss the Schiff base bond formation between polymeric networks, which explains the self-healing phenomenon. These bonds have induced 100% recovery in optimal cases.

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9.
Comparisons were made between three sets of meteorological fields used to support air quality predictions for the California Regional Particulate Air Quality Study (CRPAQS) winter episode from December 15, 2000 to January 6, 2001. The first set of fields was interpolated from observations using an objective analysis method. The second set of fields was generated using the WRF prognostic model without data assimilation. The third set of fields was generated using the WRF prognostic model with the four-dimensional data assimilation (FDDA) technique. The UCD/CIT air quality model was applied with each set of meteorological fields to predict the concentrations of airborne particulate matter and gaseous species in central California. The results show that the WRF model without data assimilation over-predicts surface wind speed by ~30% on average and consequently yields under-predictions for all PM and gaseous species except sulfate (S(VI)) and ozone(O3). The WRF model with FDDA improves the agreement between predicted and observed wind and temperature values and consequently yields improved predictions for all PM and gaseous species. Overall, diagnostic meteorological fields produced more accurate air quality predictions than either version of the WRF prognostic fields during this episode. Population-weighted average PM2.5 exposure is 40% higher using diagnostic meteorological fields compared to prognostic meteorological fields created without data assimilation. These results suggest diagnostic meteorological fields based on a dense measurement network are the preferred choice for air quality model studies during stagnant periods in locations with complex topography.  相似文献   
10.
Environmental Science and Pollution Research - Heavy metals (HMs) being the notorious and toxic are being introduced into the environment credited to natural and anthropogenic activities. The use...  相似文献   
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