全国站

热门城市 | 全国 北京 上海 广东

华北地区 | 北京 天津 河北 山西 内蒙古

东北地区 | 辽宁 吉林 黑龙江

华东地区 | 上海 江苏 浙江 安徽 福建 江西 山东

华中地区 | 河南 湖北 湖南

西南地区 | 重庆 四川 贵州 云南 西藏

西北地区 | 陕西 甘肃 青海 宁夏 新疆

华南地区 | 广东 广西 海南

资    源
  • 资    源
当前位置:查字典高考网>本科留学>托福阅读>新托福阅读复习材料:美国科学文摘精选(三)

新托福阅读复习材料:美国科学文摘精选(三)

来自:查字典高考网 2014-12-25

PMEL

ORNL/CDIAC-115

Comparison of the Carbon System Parameters at the Global CO2 Survey Crossover

Locations in the North and South Pacific Ocean, 1990-1996

As a collaborative program to measure global ocean carbon inventories and provide estimates of the anthropogenic carbon dioxide (CO2) uptake by the oceans, the National Oceanic and Atmospheric Administration and the U.S. Department of Energy have sponsored the collection of ocean carbon measurements as part of the World Ocean Circulation Experiment and Ocean-Atmosphere Carbon Exchange Study cruises. The cruises discussed here occurred in the North and South Pacific from 1990 through 1996. The carbon parameters from these 30 crossover locations have been compared to ensure that a consistent global data set emerges from the survey cruises. The results indicate that for dissolved inorganic carbon,fugacity of CO2, and pH, the agreements at most crossover locations are well within the design specifications for the global CO2 survey; whereas, in the case of total alkalinity, the agreement between crossover locations is not as close.

1. INTRODUCTION

Human activity is rapidly changing the trace gas composition of the earths atmosphere, apparently causing greenhouse warming from excess carbon dioxide (CO2) along with other trace gas species, such as water vapor, chlorofluorocarbons (CFCs), methane, and nitrous oxide. These gases play a critical role in controlling the earths climate because they increase the infrared opacity of the atmosphere, causing the planetary surface to warm. Of all the anthropogenic CO2 that has ever been produced, only about half remains in the atmosphere; it is the missing CO2 for which the global ocean is considered to be the dominant sink for the man-made increase. Future decisions on regulating emissions of greenhouse gases should be based on more accurate models that have been adequately tested against a well-designed system of measurements. Predicting global climate change, as a consequence of CO2 emissions, requires coupled atmosphere/ocean/terrestrial biosphere models that realistically simulate the rate of growth of CO2 in the atmosphere, as well as its removal, redistribution, and storage in the oceans and terrestrial biosphere. The construction of a believable present-day carbon budget is essential for the skillful prediction of atmospheric CO2 and temperature from given emission scenarios.

The worlds oceans, widely recognized to be the major long-term control on the rate of CO2 increases in the atmosphere, are believed to be absorbing about 2.0 GtC yr-1 (nearly 30 to 40% of the annual release from fossil fuels). Our present

understanding of oceanic sources and sinks for CO2 is derived from a combination of field data, that are limited by sparse temporal and spatial coverage, and model results that are validated by comparisons with oceanic bomb 14C profiles. CO2 measurements taken on the World Ocean Circulation Experiment (WOCE) cruises, which began in 1990, have provided an accurate benchmark of the ocean inventory of CO2 and other properties. These measurements were cosponsored by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Department of Energy (DOE) via the U.S. Joint Global Ocean Flux Study (JGOFS) Program. Investigators supported by these funding agencies have collaborated to examine data collected during the WOCE and Ocean-Atmosphere Carbon Exchange Study (OACES) cruises. This report addresses the consistency of oceanic carbon dioxide system parameters during 1990-1996 in the North and South Pacific.

The four parameters of the oceanic carbon dioxide system are dissolved inorganic carbon (DIC), fugacity of CO2 (fCO2), total alkalinity (TAlk), and pH. This report compares the carbon system parameters, along with salinity and dissolved oxygen (O2), against sigma theta () where cruises overlapped throughout the Pacific Ocean basin. Similar comparisons have been made for oceanic carbon in the Indian Ocean (Johnson et al. 1998; Millero et al. 1998). In addition, comparisons of nutrient data have been compiled (Gordon et al. 1998). The cruise data for this report will be made available through the OACES and the Carbon Dioxide Information Analysis Center (CDIAC) data management centers.

The Pacific Ocean cruises occurred from 1990-1996, and data have been compared at 30 locations where cruises overlapped in the North and South Pacific Ocean (Fig. 1). We do not address survey stations in the Pacific where no crossovers occurred. In addition, carbon and hydrographic data collected during some of the Pacific expedition cruises (i.e., P2, P12, and S4I) were not available in time for this report.

2. ANALYTICAL METHODS

Analyses of all carbon parameters were performed following the techniques outlined in the Handbook of Methods for the Analysis of the Various Parameters of the Carbon Dioxide System in Sea Water (DOE 1994). Certified Reference Materials (CRMs) were used on all cruises as secondary standards for DIC, unless otherwise noted. Discussion of the preparation and use of CRMs is available in detail (UNESCO 1991; Dickson 1992; Dickson, Anderson, and Afghan, unpublished manuscript; Dickson, Afghan, and Anderson, unpublished manuscript). These materials consisted of a matrix of natural, sterile seawater. They were bottled in large batches into 500-mL borosilicate glass containers, sealed to prevent contamination, and shipped to the institutes participating in this study. These secondary standards were then analyzed at sea over the course of each of the cruises as a means to verify accuracy. Certification of the reference material

for DIC is based on manometric analyses in the shore-based laboratory of Charles D. Keeling of Scripps Institution of Oceanography (SIO) over a period of several months (UNESCO 1991; Guenther 1994; Keeling, C. D., personal communication, 1999). Since CRMs were analyzed routinely for DIC during most cruises used in this report, all groups analyzing for TAlk on those cruises subsequently analyzed CRMs as well; this enabled post-cruise corrections to be

made to the TAlk data based on archived samples that were analyzed at Dr. Keelings laboratory at SIO. CRMs were not available for any other carbon parameter discussed in this report. Analyses of salinity and O2 followed WOCE Hydrographic Program (WHP) protocol (WOCE 1994).

3. RESULTS AND DISCUSSION

3.1 Statistical Methods

Tables 1 and 2 summarize the crossover sites and parameters measured, and Tables 3, 4, 5, and 6 are summaries of the statistical data for each parameter at the crossover locations. Eleven laboratories from two countries participated in this comparison study that examines crossovers in both the North and South Pacific. At some of the crossover locations, the site was occupied on more than one occasion [i.e., the crossover at 170?W and 10?S was frequented by NOAA on three different cruises (CGC90, EqS92, and P15S), as well as by the Institute of Ocean

Science (IOS) (P15N) and the University of Hawaii (UH) (P31)]. A total of 30 crossover locations were studied in this analysis and 41 individual crossover comparisons were made. Individual plots of each carbon parameter, along with salinity and O2, were first created for every crossover against using data from the entire water column (Appendix A). Only data sets that showed good agreement in both salinity and O2 data were used for the comparisons. An expanded area within the plot was examined further based on the region of reasonable agreement of the vs salinity plot. In most cases, 27.0 was used in the expanded regions.

A curve-fitting routine was applied to the expanded plots (Appendix A) using a second-order polynomial fit (unless otherwise noted in Tables 3, 4, 5, and 6). The difference between each region of crossover was calculated based on evenly distributed intervals on the axis; the intervals chosen were, on average, 0.04 units apart. In the case where more than one station on a given cruise was computed at a particular crossover location, averages of the resulting fits of the two or more stations for that cruise were determined, and the total mean of the differences over the entire range was compared. This procedure was performed for every carbon parameter measured (Tables 3, 4, 5, and 6). The mean and standard deviation of the differences were computed, along with the mean and standard deviation of the absolute value of the differences. For the DIC data, the results were calculated both uncorrected and corrected using the CRMs as a basis for the corrections.

3.2 Cruise Results

The most detailed carbon parameter results are for DIC, as this parameter was measured on all of the cruises (Table 3). The next most frequently measured parameter was fCO2, followed by TAlk and pH (Tables 4, 5, and 6), respectively.

DIC CRMs were available to the investigators for almost every cruise during the survey. In general, there is excellent agreement between DIC data sets at the crossover locations. At the beginning of the program, the goal was to obtain

agreements between cruises that were less than 4.0 mol/kg. On 31 of 41 crossover comparisons the uncorrected DIC differences were less than this value, and on 24 of the comparisons the differences were less than 2.0 mol/kg.

Most of the cruises that did not meet this criteria occurred at the beginning of the program when methods were still being developed, and one comparison was during a strong El Nio event where the upper water column hydrography was

significantly different from normal (Feely et al. 1995). When the DIC data were corrected for CRMs, 36 of the 41 comparisons were less than 4.0 mol/kg, and 31 comparisons were less than 2.0 mol/kg. The mean of the absolute value of the differences was 2.4 2.8 mol/kg for the uncorrected data and 1.9 2.3 mol/kg

for the corrected data (Fig. 2). For a mean DIC concentration of approximately 2260 mol/kg in the deep Pacific, this difference is equivalent to an uncertainty of approximately 0.08%. The excellent agreement of the DIC data was

likely due primarily to the use of the coulometer (UIC, Inc.) coupled with a SOMMA (Single Operator Multiparameter Metabolic Analyzer) inlet system developed by Ken Johnson (Johnson et al. 1985, 1987, 1993; Johnson 1992) of Brookhaven National Laboratory (BNL), as well as the use of CRMs as secondary standards during the cruises. The spirit of cooperation and close interactions among the scientists and technicians who were responsible for the measurements also

contributed to the outstanding quality of the data set.

The crossover comparison of fCO2 in seawater is not as straightforward as the comparison of the other carbon parameters because the measurement temperature for fCO2 differs for different cruises. The comparison thus requires a temperature normalization, which is performed by using the carbonate dissociation constants, and measured DIC. For comparison purposes, all values were normalized to 20癈 in this report. The normalization is dependent on the dissociation constant used. In this comparison, we used the constants of Mehrbach et al. (1973) as refitted by Dickson and Millero (1987). An example of the effect of constants on the final comparison is given in Table 7 in which we use typical deep-sea DIC and fCO2 values as found in the southeastern Pacific. Also included in the table are the fCO2@20癈/DIC values in atm/(mol/kg to illustrate the sensitivity of discrete fCO2 measurements relative to DIC in deep waters.

We analyzed 16 crossover comparisons for fCO2, and observed differences ranging between -28.7 and 34 atm, excluding the large difference during the 1992 El Nio at 5?N, 110?W. The mean of the absolute value of the difference was 17.6 16.3 atm. In deep water 10 atm of fCO2 measured at 20癈 is approximately equivalent to an uncertainty of 1.5 mol/kg DIC. Thus, with the possible exception of two or three crossover locations, the systematic differences in the fCO2 data corresponded to a similar uncertainty to that of the majority of the DIC results. Since there were no CRMs available for fCO2 during the Pacific expeditions, the analysts used their own compressed gas standards for the measurements. Some of the differences between the data sets may have resulted from systematic differences etween standards and/or differences between methods employed.

The agreement of the TAlk data between the 15 crossover locations is not quite as good as the DIC results. The differences between cruises ranged from -11.5 to 7.8 mol/kg; generally, the smallest differences correspond to the excellent agreement by the same laboratory on different cruises. As with DIC and fCO2, the largest offsets generally occur during the strong El Nino event in 1992. The mean of the absolute value of the difference was 5.7 3.3 mol/kg; this corresponds to a mean uncertainty of approximately 0.2%. CRMs were available for TAlk where crossover comparisons were made for this report, and all data have been normalized to the certified values. Three laboratories performed pH analyses, and as a result, only five crossover locations were available to compare the pH results. All comparisons were made on the total seawater scale. The differences ranged from -0.0005 to 0.0062 and the mean of the absolute value of the difference was 0.0023 0.0025. In the deep Pacific, an uncertainty of 1 mol/kg DIC is equivalent to approximately 0.003 pH units. These results suggest that the limited amount of pH data in the Pacific were in excellent agreement with each other.

The summary data in Tables 3, 4, 5, and 6 should be viewed as one of several indicators of the overall quality of the carbon data from the Pacific. In addition to these results, there also are the shore-based analyses of replicate DIC samples taken during each of the cruises (Guenther et al. 1994) and the interlaboratory analyses of the CRMs (Dickson 1992). These three pieces of information should be used together with thermodynamic models in the process of evaluating the overall quality of the database. In several cases, particularly with respect to the NOAA data sets, three or four carbon parameters were measured during the cruises. In these situations, the internal consistency of the individual parameters in the data sets can be checked using an appropriate thermodynamic model (Millero et al. 1993; Byrne et al., in press; Wanninkhof et al., 1999). In this way, two parameters may be used to check the validity of the third and, in some cases, fourth parameter. For example, very precise and accurate DIC and pH data may be used to validate the fCO2 and TAlk data. We recommend that individual data sets be evaluated in this manner before they are used in physical and biogeochemical models. In addition, it is our recommendation that DIC data are reported to the database manager as both uncorrected and corrected with respect to CRMs, and that the CRM results are appended in a meta file. This file should contain at minimum CRM batch number, number of CRMs run, the given value and observed values, along with the standard deviation and number of CRM results rejected. The method of correction of the data should be clearly described, including if the correction was applied per cell, per cruise, using a longer-term mean, or if the correction was an additive or a ratio. In order to obtain a coherent data set of DIC from this program, it is imperative that the data be corrected in the same way. As shown in this report, the crossover data for DIC are statistically improved when the correction is applied. We also recommend the TAlk data be reported to the database manager in a similar way, appending a meta file containing a description of the CRM results. In addition, it is useful for both CRM corrected and uncorrected TAlk data to be submitted.

4. CONCLUSIONS

The comparison of the carbon system parameters during the WOCE and OACES cruises in the North and South Pacific has provided unique information on data quality at the crossover locations. For DIC, fCO2, and pH, the agreement at most crossover locations is well within the design specifications for the global CO2 survey, despite the lack of CRMs for both fCO2 and pH. In a statistical analysis performed on DIC data that were corrected to CRM values vs noncorrected values, results indicate there is a significant difference between the two. On the other hand, although normalized to CRM values for TAlk, the comparisons made in this report for that parameter were not as good. The outcome of this comparison stresses the importance of CRMs, as well as the value of building some redundant measurements into the program to provide an independent check on data quality.

Since the inception of this document, we have made every attempt to include the most up-to-date information available; however, large data sets are constantly evolving. Some of the data presented in this report are expected to change as the data are further evaluated. To access the latest data sets, please check the web sites listed in Section 5.

【新托福阅读复习材料:美国科学文摘精选(三)】相关文章:

托福阅读:动物学词汇

托福备考阅读心得:做题要保持清醒的思路

评:首次新托福阅读听力考查题材广泛

托福阅读新旧题型比较及应对技巧-2

托福阅读满分经验分享

如何灵活应对托福阅读中学术词汇

2007托福考试阅读模拟试题训练(三)

托福(toefl)阅读考试知识(二十九)

1997年1月托福阅读全真考题

新托福阅读复习材料:美国科学文摘精选(一)

[标签:海外留学,语言考试,托福,,]

网友关注

解读清华大学2013年保送生选拔方式三大特点

经验分享:揭秘清华工科男保送生不为人知的一面

北师大实验中学高三12名学生保送清华和北大

知名博主:浅谈2012年北京保送生资格来源和中学来源

2013年清华大学保送生报名时间及方式

陕西省公示高校招收保送生及高水平运动员名单

河北:2012年普通高等学校招收保送生办理程序

2014年外语类保送生将成高校保送生主力军

2012年深圳中学21人保送清华北大(图)

中国科技大学2013年保送生招生政策有变化

奥赛退热:高考不再保送奥赛获奖选手

武汉二中保送招生出新规:不孝敬父母者不得报考

西安电子科技大学2013年保送生选拔条件

清华招办主任谈2014年奥赛保送资格取消后的高招制度变革

兰州大学2013年保送生网上报名注意事项

北京大学2013年保送生招生仍以中学推荐为主

山东高中生可自荐中科大 保送不成可参加自主招生

2013年北京语言大学十余个语种招收保送生

中国高考保送招生制度存废引发争议

中国科技大学已公布2013年保送生和少年班招生简章

厦门大学2013年将不再单招奥赛保送生

新疆喜讯:理科三名保送生首批收到被清华录取通知书(图)

清华大学2013年保送生报名开始 笔试内容有微调

北京大学2013年8个小语种招生保送生42人

揭秘保送清华北大学子背后的秘密(组图)

清华大学2013年保送生考试笔试及面试时间

高考保送生近3成来自省会 农村学子处劣势

河南:2014年高考不再保送全国奥赛获奖者

保送生快报:2013年高校保送生报名时间汇总

清华2013保送生考试按专业志向进行笔试选拔

网友关注视频

老师好:这大概是高考前所有班主任都会干的事,取消一切副课!

创艺第二届:2019届高考录取表彰大会暨“核桃音乐节”合影——你只管努力,剩下的交给创艺

组合名师余老师在线讲解2019高考数学全国3卷理科16题

看懂图片,你也会做高考地理题,解析2019年高考文综地理4

张雪峰高考志愿填报指南 第15集 高考填报志愿,想学电子信息类专业,推荐报这六所高校,不出错

这!就是专业 第15集 中国矿业大学——数学专业

【高考英语】七选五解析,不算太难

高考作文:全国2卷 材料作文破题分析 2019高考助力

这!就是专业 第1集 川农动物科学专业解读

高中信息技术

男孩考上理想大学,却因为网瘾休学在家,高中班主任上门劝导

学渣男高考英语全写B,老师给老爸说成绩,老爸直接听懵了!

高考政治一轮:《经济生活》第九课(社会主义市场经济)练习

高考阅卷名师给考生的高考作文密训课 第5集 高考作文审题实操方法精讲(三)

衍声高考琴行2019高本硕学生暑假音乐会 张俊瀚《陕北民歌主题变奏曲》《阿根廷舞曲》第三乐章

你高考成绩高吗?这道题目怎能成立?高难度奥数,能不能把你难住

amc传媒音乐影像 第一季 第598集 西安原创乐队走进英泰青卓 用音乐助力高考学子

高考帮:这!就是专业 第8集 安徽师范大学

新闻早报 2019 高考前最后一课 合唱送给班主任

老外:外国理科高材生遇到中国数学高考,看到题目狂喊:NO!

沈阳音乐学院郎亦农教授的女高音高考曲目解析课程 第9集 《赛吾里麦》演唱讲解,音乐表现一定要自然流畅

盘点今年最难的高考数学题

高考帮:招办面对面 第55集 上海视觉艺术学院

高级中学高考试卷分析专题教研会

美术联考用纸上海考试模拟试卷纸高考统考纸 4k水粉纸素描纸 速写纸卡纸美术模拟测试试卷纸 美术考试专用纸

广州早晨 2019 山西一高中班主任带学生骑行1800公里去上海

知道班里的高考成绩后,山东班主任气吐血了

女儿高考作文只得5分,怎料妈妈一听作文题目,瞬间懂了

葛军大爷怒了:高考我出了个小学数学送分题,你们跟我说不会做?

爆笑班主任 第一季 第221集 高考结束学生有多疯狂?山东王老师疯狂吐槽