National Ambient Air Quality Standards (NAAQS) (Added 8/8/2021)
Extracted from the United States Environmental Protection Agency (EPA) NAAQS Table The Clean Air Act, which was last amended in 1990, requires EPA to set National Ambient Air Quality Standards (40 CFR part 50) for six principal pollutants ("criteria" air pollutants) which can be harmful to public health and the environment. The Clean Air Act identifies two types of national ambient air quality standards. Primary standards provide public health protection, including protecting the health of "sensitive" populations such as asthmatics, children, and the elderly. Secondary standards provide public welfare protection, including protection against decreased visibility and damage to animals, crops, vegetation, and buildings. Periodically, the standards are reviewed and sometimes may be revised, establishing new standards. The most recently established standards are listed below. In some areas of the U.S., certain regulatory requirements may also remain for implementation of previously established standards. Units of measure for the standards are parts per million (ppm) by volume, parts per billion (ppb) by volume, and micrograms per cubic meter of air (µg/m 3 ). (1) In areas designated non-attainment for the Pb standards prior to the promulgation of the current (2008) standards, and for which implementation plans to attain or maintain the current (2008) standards have not been submitted and approved, the previous standards (1.5 µg/m 3 as a calendar quarter average) also remain in effect. (2) The level of the annual NO 2 standard is 0.053 ppm. It is shown here in terms of ppb for the purposes of clearer comparison to the 1-hour standard level. (3) Final rule signed October 1, 2015, and effective December 28, 2015. The previous (2008) O 3 standards are not revoked and remain in effect for designated areas. Additionally, some areas may have certain continuing implementation obligations under the prior revoked 1-hour (1979) and 8-hour (1997) O 3 standards. (4) The previous SO 2 standards (0.14 ppm 24-hour and 0.03 ppm annual) will additionally remain in effect in certain areas: (1) any area for which it is not yet 1 year since the effective date of designation under the current (2010) standards, and (2)any area for which an implementation plan providing for attainment of the current (2010) standard has not been submitted and approved and which is designated nonattainment under the previous SO 2 standards or is not meeting the requirements of a SIP call under the previous SO 2 standards (40 CFR 50.4(3)). A SIP call is an EPA action requiring a state to resubmit all or part of its State Implementation Plan to demonstrate attainment of the required NAAQS. Menu of Control Measures for NAAQS Implementation The Menu of Control Measures (MCM) provides state, local and tribal air agencies with the existing emission reduction measures as well as relevant information concerning the efficiency and cost effectiveness of the measures. State, local and tribal agencies will be able to use this information in developing emission reduction strategies, plans and programs to assure they attain and maintain the National Ambient Air Quality Standards (NAAQS). The MCM is a living document that can be updated with newly available or more current data as it becomes available. Menu of Control Measures Posted: 8/8/2021
Pollutant [Links to historical tables of NAAQS reviews
Primary/ Secondary
Averaging Time
Level
Form
Carbon Monoxide (CO)
primary
8 hours 1 hour
9 ppm 35 ppm
Not to be exceeded more than once per year
Lead (Pb)
primary and secondary
Rolling 3 month average
0.15 mg/m 3 (1)
Not to be exceeded
Nitrogen Dioxide (NO 2 )
primary primary and secondary
1 hour 1 year
100 ppb 53 ppb (2)
98th percentile of 1 hour daily maximum concentrations, averaged over 3 years Annual Mean
Ozone (O 3 )
primary and secondary
8 hours
0.070 ppm (3)
Annual fourth-highest daily maximum 8- hour concentration, averaged over 3 years
Particle Pollution (PM)
PM 2.5 primary secondary primary and secondary PM 10 primary and secondary
1 year 1 year 24 hours 24 hours
12.0 mg/m 3 15.0 mg/m 3 35 mg/m 3 150 mg/m 3
annual mean, averaged over 3 years annual mean, averaged over 3 years 98th percentile, averaged over 3 years Not to be exceeded more than once per year on average over 3 years
Sulfur Dioxide (SO 2 )
primary secondary
1 hour 3 hours
75 ppb (4) 0.5 ppm
99th percentile of 1-hour daily maximum concentrations, averaged over 3 years Not to be exceeded more than once per year
HEAT INDEX FORMULA (Updated 15 February 2019) The Heat Index "Equation" (or, More Than You Ever Wanted to Know About Heat Index) Lans P. Rothfusz Scientific Services Division NWS Southern Region Headquarters, Fort Worth, TX
When summer spreads its oppressive ridge over most of the United State's Southern Region, NWS phones ring off their hooks with questions about the Heat Index. Many questions regard the actual equation used in calculating the Heat Index. Some callers are satisfied with the response that it is extremely complicated. Some are satisfied with the nomogram (see chart).
Chart by Lans Rothfusz, MIC at NWS Tulsa, OK
But, there are a few who will settle for nothing less than the equation itself. No true equation for the Heat Index exists. Heat Index values are derived from a collection of equations that comprise a model. This Technical Attachment presents an equation that approximates the Heat Index and, thus, should satisfy the latter group of callers. The Heat Index (or apparent temperature) is the result of extensive biometeorological studies. The parameters involved in its calculation are shown below (from Steadman, 1979). Each of these parameters can be described by an equation but they are given assumed magnitudes (in parentheses) in order to simplify the model. # Vapor pressure. Ambient vapor pressure of the atmosphere. (1.6 kPa) # Dimensions of a human. Determines the skin's surface area. (5' 7" tall, 147 pounds) # Effective radiation area of skin. A ratio that depends upon skin surface area. (0.80) # Significant diameter of a human. Based on the body's volume and density. (15.3 cm) # Clothing cover. Long trousers and short-sleeved shirt is assumed. (84% coverage) # Core temperature. Internal body temperature. (98.6°F) # Core vapor pressure. Depends upon body's core temperature and salinity. (5.65 kPa) # Surface temperatures and vapor pressures of skin and clothing. Affects heat transfer from the skin's surface either by radiation or convection. These values are determined by an iterative process. # Activity. Determines metabolic output. (180 W m-2 of skin area for the model person walking outdoors at a speed of 3.1 mph) # Effective wind speed. Vector sum of the body's movement and an average wind speed. Angle between vectors influences convection from skin surface (below). (5 kts) # Clothing resistance to heat transfer. The magnitude of this value is based on the assumption that the clothing is 20% fiber and 80% air. # Clothing resistance to moisture transfer. Since clothing is mostly air, pure vapor diffusion is used here. # Radiation from the surface of the skin. Actually, a radiative heat-transfer coefficient determined from previous studies. # Convection from the surface of the skin. A convection coefficient also determined from previous studies. Influenced by kinematic viscosity of air and angle of wind. # Sweating rate. Assumes that sweat is uniform and not dripping from the body. As an aside, these assumptions are important for the forecaster to keep in mind. For example, a common perception is that wind is not taken into account in the Heat Index. In actuality it is. It is assumed to be 5 knots. This may seem trivial but a forecaster may be able to use this information creatively when writing Public Information Statements regarding heat stress, heat stroke, etc. # Ventilation rate. The amount of heat lost via exhaling. (2-12%, depending upon humidity) # Skin resistance to heat transfer. A function of activity, skin temperature, among others. # Skin resistance to moisture transfer. A function of the vapor-pressure difference across the skin (and, therefore, relative humidity). It decreases with increasing activity. # Surface resistance to heat transfer. As radiation and convection from the skin increases, this value decreases. # Surface resistance to moisture transfer. Similar to heat transfer resistance but also depends upon conditions in the boundary layer just above skin's surface. These last five variables are used explicitly to derive the apparent temperature. By an iterative procedure which relies on the assumptions in the first list, the model is reduced to a relationship between dry bulb temperature (at different humidities) and the skin's resistance to heat and moisture transfer. Since these resistances are directly related to skin temperature, we now have a relationship between ambient temperature and relative humidity versus skin (or apparent) temperature. As a result of this procedure, there is a base relative humidity at which an apparent temperature (e.g., 90°F) "feels" like the same air temperature (90°F). Increasing (decreasing) humidity and temperature result in increasing (decreasing) apparent temperature, and, yes, apparent temperature can be lower than air temperature. Steadman (1979) developed a table based on this relationship and the nomogram (above) summarizes that table. In order to arrive at an equation which uses more conventional independent variables, a multiple regression analysis was performed on the data from Steadman's table. The resulting equation could be considered a Heat Index equation, although it is obtained in a "round- about" way. Thus, here is an ersatz version of the Heat Index equation: HI = -42.379 + 2.04901523T + 10.14333127R - 0.22475541TR - 6.83783x10 -3T2 -5.481717x10 -2R2 + 1.22874x10 -3T2R + 8.5282x10 -4TR2 - 1.99x10 -6T2R2 where T = ambient dry bulb temperature (°F), R = relative humidity (integer percentage) Because this equation is obtained by multiple regression analysis, the heat index value (HI) has an error of ±1.3°F. Even though temperature and relative humidity are the only two variables in the equation, all the variables on the lists above are implied. References Steadman, R.G., 1979: The assessment of sultriness. Part I: A temperature-humidity index based on human physiology and clothing science. J. Appl. Meteor., 18, 861-873.