Microscale air quality impacts of distributed power generation facilities

The electric system is experiencing rapid growth in the adoption of a mix of distributed renewable and fossil fuel sources, along with increasing amounts of off-grid generation. New operational regimes may have unforeseen consequences for air quality. A three-dimensional microscale chemical transport model (CTM) driven by an urban wind model was used to assess gaseous air pollutant and particulate matter (PM) impacts within ~10 km of fossil-fueled distributed power generation (DG) facilities during the early afternoon of a typical summer day in Houston, TX. Three types of DG scenarios were considered in the presence of motor vehicle emissions and a realistic urban canopy: (1) a 25-MW natural gas turbine operating at steady state in either simple cycle or combined heating and power (CHP) mode; (2) a 25-MW simple cycle gas turbine undergoing a cold startup with either moderate or enhanced formaldehyde emissions; and (3) a data center generating 10 MW of emergency power with either diesel or natural gas-fired backup generators (BUGs) without pollution controls. Simulations of criteria pollutants (NO₂, CO, O₃, PM) and the toxic pollutant, formaldehyde (HCHO), were conducted assuming a 2-hr operational time period. In all cases, NO_x titration dominated ozone production near the source. The turbine scenarios did not result in ambient concentration enhancements significantly exceeding 1 ppbv for gaseous pollutants or over 1 µg/m³ for PM after 2 hr of emission, assuming realistic plume rise. In the case of the datacenter with diesel BUGs, ambient NO₂ concentrations were enhanced by 10–50 ppbv within 2 km downwind of the source, while maximum PM impacts in the immediate vicinity of the datacenter were less than 5 µg/m³.

Implications: Plausible scenarios of distributed fossil generation consistent with the electricity grid’s transformation to a more flexible and modernized system suggest that a substantial amount of deployment would be required to significantly affect air quality on a localized scale. In particular, natural gas turbines typically used in distributed generation may have minor effects. Large banks of diesel backup generators such as those used by data centers, on the other hand, may require pollution controls or conversion to natural gas-fired reciprocal internal combustion engines to decrease nitrogen dioxide pollution.     

Central power generation versus distributed generation – An air quality assessment in the South Coast Air Basin of California

This study assesses the air quality impacts of central power generation and compares them with the impacts of distributed generation (DG). The central power plant emissions factors used are from a newly installed combined cycle gas turbine system. Because location of power plants is a key parameter affecting air quality impacts, this study considers three potential locations for the installation of central power plants. Air quality impacts are evaluated for the South Coast Air Basin of California, in the year 2010, using a three-dimensional air quality model. Results are compared to air quality impacts from two potential DG scenarios to meet the same power demand as that of the central power plant case.Even though emissions from central generation are lower than emissions from the DG technology mix considered herein, central generation concentrates emissions in a small area, whereas DG spreads emissions throughout a larger cross-section of the air basin. As a result, air quality impacts from central generation are more significant than those from DG. The study also shows that assessment of air quality impacts from distributed and central generation should not only consider emissions levels, but also the spatial and temporal distribution of emissions and the air quality that results from atmospheric chemistry and transport – highly non-linear processes.Finally, analysis of population exposure to ozone and PM_2.5 shows that central generation located in coastal areas upwind from populated areas would cause the highest population exposure and even though emissions from central generation are considerably lower than DG emissions spread throughout the basin, results show that central generation causes a higher pollutant exposure than DG.     

Assessment of the emissions and air quality impacts of biomass and biogas use in California

It is estimated that there is sufficient in-state “technically” recoverable biomass to support nearly 4000 MW of bioelectricity generation capacity. This study assesses the emissions of greenhouse gases and air pollutants and resulting air quality impacts of new and existing bioenergy capacity throughout the state of California, focusing on feedstocks and advanced technologies utilizing biomass resources predominant in each region. The options for bioresources include the production of bioelectricity and renewable natural gas (NG). Emissions of criteria pollutants and greenhouse gases are quantified for a set of scenarios that span the emission factors for power generation and the use of renewable natural gas for vehicle fueling. Emissions are input to the Community Multiscale Air Quality (CMAQ) model to predict regional and statewide temporal air quality impacts from the biopower scenarios. With current technology and at the emission levels of current installations, maximum bioelectricity production could increase nitrogen oxide (NO_x) emissions by 10% in 2020, which would cause increases in ozone and particulate matter concentrations in large areas of California. Technology upgrades would achieve the lowest criteria pollutant emissions. Conversion of biomass to compressed NG (CNG) for vehicles would achieve comparable emission reductions of criteria pollutants and minimize emissions of greenhouse gases (GHG). Air quality modeling of biomass scenarios suggest that applying technological changes and emission controls would minimize the air quality impacts of bioelectricity generation. And a shift from bioelectricity production to CNG production for vehicles would reduce air quality impacts further. From a co-benefits standpoint, CNG production for vehicles appears to provide the best benefits in terms of GHG emissions and air quality.

Implications:?This investigation provides a consistent analysis of air quality impacts and greenhouse gas emissions for scenarios examining increased biomass use. Further work involving economic assessment, seasonal or annual emissions and air quality modeling, and potential exposure analysis would help inform policy makers and industry with respect to further development and direction of biomass policy and bioenergy technology alternatives needed to meet energy and environmental goals in California.     

Evaluation of the European population intake fractions for European and Finnish anthropogenic primary fine particulate matter emissions

The intake fraction (iF) has been defined as the integrated incremental intake of a pollutant released from a source category or region summed over all exposed individuals. In this study we evaluated the iFs in the population of Europe for emissions of anthropogenic primary fine particulate matter (PM_2.5) from sources in Europe, with a more detailed analysis of the iF from Finnish sources. Parameters for calculating the iFs include the emission strengths, the predicted atmospheric concentrations, European population data, and the average breathing rate per person. Emissions for the whole of Europe and Finland were based on the inventories of the European Monitoring and Evaluation Programme (EMEP) and the Finnish Regional Emission Scenario (FRES) model, respectively. The atmospheric dispersion of primary PM_2.5 was computed using the regional-scale dispersion model SILAM. The iFs from Finnish sources were also computed separately for six emission source categories. The iFs corresponding to the primary PM_2.5 emissions from the European countries for the whole population of Europe were generally highest for the densely populated Western European countries, second highest for the Eastern and Southern European countries, and lowest for the Northern European and Baltic countries. For the entire European population, the iF values varied from the lowest value of 0.31 per million for emissions from Cyprus, to the highest value of 4.42 per million for emissions from Belgium. These results depend on the regional distribution of the population and the prevailing long-term meteorological conditions. Regarding Finnish primary PM_2.5 emissions, the iF was highest for traffic emissions (0.68 per million) and lowest for major power plant emissions (0.50 per million). The results provide new information that can be used to find the most cost-efficient emission abatement strategies and policies.     

Intake fraction distributions for benzene from vehicles in the Helsinki metropolitan area

The intake fraction (iF) gives a measure of the portion of a source's emissions that is inhaled by an exposed population over a defined period of time. This study examines spatial and population-based iF distributions of a known human carcinogen, benzene, from a ubiquitous urban source, local vehicular traffic, in the Helsinki Metropolitan Area using three computational methods. The first method uses the EXPAND model (EXPosure to Air pollution, especially to Nitrogen Dioxide and particulate matter), which incorporates spatial and temporal information on population activity patterns as well as urban-scale and street canyon dispersion models to predict spatial population exposure distributions. The second method uses data from the personal monitoring study EXPOLIS (Air Pollution Exposure Distributions of Adult Urban Populations in Europe) to estimate the intake fractions for individuals in the study. The third method, a one-compartment box model provides estimates within an order-of-magnitude or better for non-reactive agents in an urban area. Population intake fractions are higher using the personal monitoring data method (median iF 30 per million, mean iF 39 per million) compared with the spatial model (annual mean iF 10 per million) and the box model (median iF 4 per million, mean iF 7 per million). In particular, this study presents detailed intake fraction distributions on several different levels (spatial, individual, and generic) for the same urban area.     

Spatial patterns of mobile source particulate matter emissions-to-exposure relationships across the United States

Assessing the public health benefits from air pollution control measures is assisted by understanding the relationship between mobile source emissions and subsequent fine particulate matter (PM_2.5) exposure. Since this relationship varies by location, we characterized its magnitude and geographic distribution using the intake fraction (iF) concept. We considered emissions of primary PM_2.5 as well as particle precursors SO₂ and NO_x from each of 3080 counties in the US. We modeled the relationship between these emissions and total US population exposure to PM_2.5, making use of a source–receptor matrix developed for health risk assessment. For primary PM_2.5, we found a median iF of 1.2 per million, with a range of 0.12–25. Half of the total exposure was reached by a median distance of 150 km from the county where mobile source emissions originated, though this spatial extent varied across counties from within the county borders to 1800 km away. For secondary ammonium sulfate from SO₂ emissions, the median iF was 0.41 per million (range: 0.050–10), versus 0.068 per million for secondary ammonium nitrate from NO_x emissions (range: 0.00092–1.3). The median distance to half of the total exposure was greater for secondary PM_2.5 (450 km for sulfate, 390 km for nitrate). Regression analyses using exhaustive population predictors explained much of the variation in primary PM_2.5 iF (R²=0.83) as well as secondary sulfate and nitrate iF (R²=0.74 and 0.60), with greater near-source contribution for primary than for secondary PM_2.5. We conclude that long-range dispersion models with coarse geographic resolution are appropriate for risk assessments of secondary PM_2.5 or primary PM_2.5 emitted from mobile sources in rural areas, but that more resolved dispersion models are warranted for primary PM_2.5 in urban areas due to the substantial contribution of near-source populations.     

Evaluating multimedia/multipathway model intake fraction estimates using POP emission and monitoring data

This paper presents a structured evaluation of a novel multimedia chemical fate and multi-pathway human exposure model for Western Europe, IMPACT 2002, using data for PCDD/F congeners. PCDD/F congeners provide an illustration of the potential use of POPs (Persistent Organic Pollutant) data for the evaluation of such models. Based on available emission estimates, model predictions with and without spatial resolution are evaluated at three different stages against monitored data: at environmental contamination levels, food exposure concentration, and in terms of human intake fractions (iF): the fraction of an emission that is taken in by the population. The iF is approximately 3.5.10(-3) for emissions of dioxin in Western Europe. This iF compares well to the traditional non-spatial multi-media/-pathway model predictions of 3.9.10(-3) for the same region and to 2.10(-3) for the USA. Approximately 95% of the intake from Western European emissions occurs within the same region, 5% being transferred out of the region in terms of food contaminants and atmospheric advective transport.     

Fine particulate matter and carbon monoxide exposure concentrations in urban street transport microenvironments

Personal exposure studies are crucial alongside microenvironment and ambient studies in order to get a better understanding of the health risks posed by fine particulate matter and carbon monoxide in the urban transport microenvironment and for making informed decisions to manage and reduce the health risks. Studies specifically assessing the PM_2.5, ultrafine particle count and carbon monoxide personal exposure concentrations of adults in an urban transport microenvironment have steadily increased in number over the last decade. However, no recent collective summary is available, particularly one which also considers ultrafine particles; therefore, we present a review of the personal exposure concentration studies for the above named pollutants on different modes of surface transportation (walking, cycling, bus, car and taxi) in the urban transport microenvironment. Comparisons between personal exposure measurements and concentrations recorded at fixed monitoring sites are considered in addition to the factors influencing personal exposure in the transport microenvironment.In general, the exposure studies examined revealed pedestrians and cyclists to experience lower fine particulate matter and CO exposure concentrations in comparison to those inside vehicles—the vehicle shell provided no protection to the passengers. Proximity to the pollutant sources had a significant impact on exposure concentration levels experienced, consequently individuals should be encouraged to use back street routes. Fixed monitoring stations were found to be relatively poor predictors of CO and PM_2.5 exposure concentration levels experienced by individuals in the urban transport microenvironment. Although the mode of transport, traffic and meteorology parameters were commonly identified as significant factors influencing exposure concentrations to the different pollutants under examination, a large amount of the exposure concentration variation in the exposure studies remained unexplained.     

The effect of commuting microenvironment on commuter exposures to vehicular emission in Hong Kong

Vehicular exhaust emission has gradually become the major air pollution source in modern cities and traffic related exposure is found to contribute significantly to total human exposure level. A comprehensive survey was conducted from November 1995 to July 1996 in Hong Kong to assess the effect of traffic-induced air pollution inside different commuting microenvironments on commuter exposure. Microenvironmental monitoring is performed for six major public commuting modes (bus, light bus, MTR, railway, tram, ferry), plus private car and roadside pavement. Traffic-related pollutants, CO, NO_x, THC and O₃ were selected as the target pollutants. The results indicate that commuter exposure is highly influenced by the choice of commuting microenvironment. In general, the exposure level in decreasing order of measured pollutant level for respective commuting microenvironments are: private car, the group consisting light bus, bus, tram and pavement, MTR and train, and finally ferry. In private car, the CO level is several times higher than that in the other microenvironments with a trip averaged of 10.1 ppm and a maximum of 24.9 ppm. Factors such as the body position of the vehicle, intake point of the ventilation system, fuel used, ventilation, transport mode, road and driving conditions were used in the analysis. Inter-microenvironment, intra-microenvironment and temporal variation of CO concentrations were used as the major indicator. The low body position and low intake point of the ventilation system of the private car are believed to be the cause of higher intake of exhaust of other vehicles and thus result in high pollution level in this microenvironment. Compared with other metropolis around the world and the Hong Kong Air Quality Objectives (HKAQO), exposure levels of commuter to traffic-related air pollution in Hong Kong are relatively low for most pollutants measured. Only several cases of exceedence of HKAQO by NO₂ were recorded. The strong prevailing wind plus the channeling effect created by the harbor, the fuel used, the relative abundance of new cars and the successful implementation of the vehicle emission control program are factors that compensate the effect of the emission source strength and thus lead to low exposure levels.     

Future Impacts of Distributed Power Generation on Ambient Ozone and Particulate Matter Concentrations in the San Joaquin Valley of California

ABSTRACT

Distributed power generation—electricity generation that is produced by many small stationary power generators distributed throughout an urban air basin—has the potential to supply a significant portion of electricity in future years. As a result, distributed generation may lead to increased pollutant emissions within an urban air basin, which could adversely affect air quality. However, the use of combined heating and power with distributed generation may reduce the energy consumption for space heating and air conditioning, resulting in a net decrease of pollutant and greenhouse gas emissions. This work used a systematic approach based on land-use geographical information system data to determine the spatial and temporal distribution of distributed generation emissions in the San Joaquin Valley Air Basin of California and simulated the potential air quality impacts using state-of-the-art three-dimensional computer models. The evaluation of the potential market penetration of distributed generation focuses on the year 2023. In general, the air quality impacts of distributed generation were found to be small due to the restrictive 2007 California Air Resources Board air emission standards applied to all distributed generation units and due to the use of combined heating and power. Results suggest that if distributed generation units were allowed to emit at the current Best Available Control Technology standards (which are less restrictive than the 2007 California Air Resources Board standards), air quality impacts of distributed generation could compromise compliance with the federal 8-hr average ozone standard in the region.

IMPLICATIONS The San Joaquin Valley is a fast growing region that demands increasing power generation to sustain the economic development, and at the same time it is one of the worst polluted areas in the United States. Hence, the region demands alternatives that minimize the air quality impacts of power generation. This paper addresses the air quality impacts of distributed generation of power, an alternative to central power generation that can potentially reduce greenhouse gas and pollutant emissions throughout the United States.     

Total Human Exposure: Basic Concepts,EPA Field Studies,and Future Research Needs

Historically, environmental regulatory programs designed to protect public health have monitored pollutants only in geophysical carrier media (for example, outdoor air, streams, soil). Field studies have identified a gap between the levels observed in geophysical carrier media and the concentrations with which people actually come into contact: their daily exposures. A new approach—Total Human Exposure (THE)—has evolved to fill this gap and provide the critical data needed for accurately assessing public health risk. The THE approach considers a three-dimensional "bubble" around each person and measures the concentrations of all pollutants contacting that bubble, either through the air, food, water, or skin. Two basic THE approaches have emerged: (1) the direct approach using probability samples of populations and measuring pollutant concentrations in the food eaten, air breathed, water drunk, and skin contacted; and (2) the indirect approach using human activity pattern-exposure models to predict population exposure distributions. Using the direct approach, EPA has conducted over 20 field studies for pollutants representing four groups—volatile organic compounds, carbon monoxide, pesticides, and particles—in 15 cities in 12 states. The indirect modeling approach has been applied to several of these pollutants. Additional research is needed in a great variety of areas. Even from the few projects completed thus far, the THE approach has yielded a rich new data base for risk assessments and has provided many surprises about the relative contribution of various pollutant sources to public health risk.     

Assessment of the impacts on health due to the emissions of Cuban power plants that use fossil fuel oils with high content of sulfur. Estimation of external costs

Fossil fuel electricity generation has been demonstrated to be a main source of atmospheric pollution. The necessity of finding out a balance between the costs of achieving a lower level of environmental and health injury and the benefits of providing electricity at a reasonable cost have lead to the process of estimating the external costs derived from these impacts and not included in the electricity prices as a quantitative measure of it that, even when there are large uncertainties involved, can be used by decision makers in the process of achieving a global sustainable development.The external costs of the electricity generation in three Cuban power plants that use fossil fuel oils with high sulfur content have been assessed. With that purpose a specific implementation of the Impact Pathways Methodology for atmospheric emissions was developed. Dispersion of atmospheric pollutants is modeled at local and regional scales in a detailed way. Health impacts include mortality and those morbidity effects that showed relation with the increment of selected pollutant concentration in national studies. The external cost assessed for the three plants was 40,588,309 USD yr⁻¹ (min./max.: 10,194,833/169,013,252), representing 1.06 USD Cent kWh⁻¹. Costs derived from sulfur species (SO₂ and sulfate aerosol) stand for 93% of the total costs.     

Association between air pollution exposure and gestational diabetes mellitus in pregnant women: a retrospective cohort study

The global prevalence of gestational diabetes mellitus (GDM) is increasing annually, and previous research reports on the relationship between exposure to air pollutants and GDM are not completely consistent. We investigated the association between air pollutant exposure and GDM in pregnant women in a retrospective cohort study in Guangzhou. We found that in the first trimester, exposure to PM_2.5 and CO showed a significant association with GDM. In the second trimester, exposure to PM₁₀ was significantly associated with GDM. In the third trimester, exposure to PM_2.5, PM₁₀, NO₂, SO₂, and CO at IQR4 (odds ratio [OR]?=?1.271, 95% confidence interval [CI]: 1.179–1.370; OR?=?1.283, 95% CI: 1.191–1.383; OR?=?1.230, 95% CI: 1.145–1.322; OR?=?1.408, 95% CI: 1.303–1.522; OR?=?1.150, 95% CI: 1.067–1.240, respectively) compared with IQR1 was positively associated with GDM. However, exposure to NO₂ was negatively associated with GDM in the first and second trimesters, and O₃ was negatively associated with GDM in the second and third trimesters. We found that the correlation between air pollutants and GDM in different trimesters of pregnancy was not completely consistent in this retrospective cohort study. During pregnancy, there may be an interaction between air pollutant exposure and other factors, such as pregnant women’s age, occupation, anemia status, pregnancy-induced hypertension status, and pregnancy season.

     

Evaluation of air quality zone classification methods based on ambient air concentration exposure

Air quality zones are used by regulatory authorities to implement ambient air standards in order to protect human health. Air quality measurements at discrete air monitoring stations are critical tools to determine whether an air quality zone complies with local air quality standards or is noncompliant. This study presents a novel approach for evaluation of air quality zone classification methods by breaking the concentration distribution of a pollutant measured at an air monitoring station into compliance and exceedance probability density functions (PDFs) and then using Monte Carlo analysis with the Central Limit Theorem to estimate long-term exposure. The purpose of this paper is to compare the risk associated with selecting one ambient air classification approach over another by testing the possible exposure an individual living within a zone may face. The chronic daily intake (CDI) is utilized to compare different pollutant exposures over the classification duration of 3 years between two classification methods. Historical data collected from air monitoring stations in Kuwait are used to build representative models of 1-hr NO₂ and 8-hr O₃ within a zone that meets the compliance requirements of each method. The first method, the “3 Strike” method, is a conservative approach based on a winner-take-all approach common with most compliance classification methods, while the second, the 99% Rule method, allows for more robust analyses and incorporates long-term trends. A Monte Carlo analysis is used to model the CDI for each pollutant and each method with the zone at a single station and with multiple stations. The model assumes that the zone is already in compliance with air quality standards over the 3 years under the different classification methodologies. The model shows that while the CDI of the two methods differs by 2.7% over the exposure period for the single station case, the large number of samples taken over the duration period impacts the sensitivity of the statistical tests, causing the null hypothesis to fail. Local air quality managers can use either methodology to classify the compliance of an air zone, but must accept that the 99% Rule method may cause exposures that are statistically more significant than the 3 Strike method.

Implications: A novel method using the Central Limit Theorem and Monte Carlo analysis is used to directly compare different air standard compliance classification methods by estimating the chronic daily intake of pollutants. This method allows air quality managers to rapidly see how individual classification methods may impact individual population groups, as well as to evaluate different pollutants based on dosage and exposure when complete health impacts are not known.     

Different exposure levels of fine particulate matter and preterm birth: a meta-analysis based on cohort studies

The previous studies estimated the association between PM_2.5 (particulate matter with aerodynamic diameter less than or equal to 2.5 μm) exposure during pregnancy and preterm birth, only considered and highlighted the hazard effects of high levels of air pollutant exposure, and underestimated that low levels of pollutant exposure might also affect pregnancy outcome. We conducted a meta-analysis of 11 cohort studies, a total of more than 1,500,000 subjects. The results of these studies were pooled by exposure levels and study periods. PM_2.5 exposure during pregnancy was positively associated with preterm birth (OR = 1.15, 95% CI = 1.07–1.23), and during the first trimester of pregnancy, low levels of PM_2.5 exposure were also positively associated with preterm birth (OR = 1.17, 95% CI = 1.04–1.30). It is important to protect pregnant women from PM_2.5 exposures, especially during their first trimester of pregnancy even when the ambient PM_2.5 concentration is relatively low. More relevant health policy should be carried out to prevent hazard effect of air pollutants.     

Chemical Characterization and Source Identification of Polycyclic Aromatic Hydrocarbons in Aerosols Originating from Different Sources

To put waste-to-energy (WTE) in perspective, it is important to see how it measures up environmentally to other power generation utility sources.

This paper compares actual WTE facility emissions with those from fossil fuel combustion utility sources. This comparison is made on an electricity production basis, such as a pound of pollutant per megawatt-hour of net electricity generated, for each power generation source.     

Sensor transition failure in the high flow sampler: Implications for methane emission inventories of natural gas infrastructure

Quantification of leaks from natural gas (NG) infrastructure is a key step in reducing emissions of the greenhouse gas methane (CH₄), particularly as NG becomes a larger component of domestic energy supply. The U.S. Environmental Protection Agency (EPA) requires measurement and reporting of emissions of CH₄ from NG transmission, storage, and processing facilities, and the high-flow sampler (or high-volume sampler) is one of the tools approved for this by the EPA. The Bacharach Hi-Flow Sampler (BHFS) is the only commercially available high-flow instrument, and it is also used throughout the NG supply chain for directed inspection and maintenance, emission factor development, and greenhouse gas reduction programs. Here we document failure of the BHFS to transition from a catalytic oxidation sensor used to measure low NG (~5% or less) concentrations to a thermal conductivity sensor for higher concentrations (from ~5% to 100%), resulting in underestimation of NG emission rates. Our analysis includes both our own field testing and analysis of data from two other studies (Modrak et al., 2012; City of Fort Worth, 2011). Although this failure is not completely understood, and although we do not know if all BHFS models are similarly affected, sensor transition failure has been observed under one or more of these conditions: (1) Calibration is more than ~2 weeks old; (2) firmware is out of date; or (3) the composition of the NG source is less than ~91% CH₄. The extent to which this issue has affected recent emission studies is uncertain, but the analysis presented here suggests that the problem could be widespread. Furthermore, it is critical that this problem be resolved before the onset of regulations on CH₄ emissions from the oil and gas industry, as the BHFS is a popular instrument for these measurements.

Implications: An instrument commonly used to measure leaks in natural gas infrastructure has a critical sensor transition failure issue that results in underestimation of leaks, with implications for greenhouse gas emissions estimates as well as safety.     

A large-scale fumigation system for investigating interactions between air pollution and cold stress on plants

A new large-scale closed chamber fumigation system with cooling facilities is described for studying effects of low concentrations of SO(2), NO(2) and O(3) and low temperatures on woody species and herbaceous plants. The system is based on modified hemispherical greenhouses with a forced air ventilation system. This provides a chamber environment with low spatial variability of pollutant gas concentrations and rapid air circulation which allows exposure of plants at near ambient temperatures and relative humidity. Large capacity cooling units come into operation when ambient temperatures fall below 0 degrees C, and these allow chamber temperatures to be lowered by an additional 4 to 8 degrees C in experiments designed to test whether exposure to pollutants enhances the frost sensitivity of plants.     

铅锌冶炼行业循环经济产业链构建

运用循环经济理论,以某铅锌冶炼企业为例,在分析企业能流、物流的基础上,研究了企业的循环经济发展潜力,提出了铅锌冶炼行业"冶炼-制酸-发电-贵金属回收"的循环经济发展产业链模式.研究结果表明,通过构建铅锌冶炼企业循环经济产业链,可以提高企业的资源利用效率,降低能耗和生产成本,减少污染物的排放,获得显著的经济效益和环境效益.