diff --git a/R/calc-limits.R b/R/calc-limits.R
index 084b1f6..2a0ab9b 100644
--- a/R/calc-limits.R
+++ b/R/calc-limits.R
@@ -7,11 +7,6 @@ join_codes <- function (x) {
   x
 }
 
-average_monthly_values <- function (x) {
-  x <- plyr::ddply(x, "Variable", average_monthly_values_variable)
-  x
-}
-
 join_limits <- function (x) {
   x$..ID <- 1:nrow(x)
   x <- dplyr::left_join(x, wqbc_limits(), by = c("Variable", "Units"))
@@ -68,56 +63,97 @@ average_conditional_code_values <- function (x) {
 fill_in_conditional_codes <- function (x, ccodes) {
   y <- dplyr::filter_(x, ~Code %in% ccodes)
   y <- plyr::ddply(y, .variables = "Code", .fun = average_conditional_code_values)
-
+  x$Conditional <- FALSE
   if(nrow(y)) {
     dates <- expand.grid(Date = unique(x$Date), Variable = unique(y$Variable),
                          stringsAsFactors = FALSE)
-    y <- dplyr::left_join(dates, y, by = c("Date", "Variable"))
+    y$Date <- NULL
+    y <- dplyr::inner_join(dates, y, by = "Variable")
     y <- dplyr::anti_join(y, x, by = c("Date", "Variable"))
-    x <- rbind(x, y)
+    if(nrow(y)) {
+      y$Conditional <- TRUE
+      x <- rbind(x, y)
+    }
   }
   x
 }
 
-calc_limits_by_date <- function (x, messages) {
+calc_limits_by_date <- function (x) {
 
   ccodes <- get_conditional_codes(x$Condition[x$Term == "Short"])
   x <- dplyr::filter_(x, ~(!is.na(Term) & Term == "Short") | Code %in% ccodes)
   x <- fill_in_conditional_codes(x, ccodes)
   x <- plyr::ddply(x, "Date", calc_limits_by_period)
+  x <- dplyr::filter_(x, ~!Conditional)
   stopifnot(!anyDuplicated(x$..ID))
   x
 }
 
-calc_limits_by_30day <- function (x) {
-  x <- dplyr::filter_(x, ~!is.na(Term) & Term == "Short")
-#  x$Year <- lubridate::year(x$Date)
- # x$Month <- lubridate::month(x$Date)
+abs_days_diff <- function (x, y) {
+  abs(as.integer(diff(c(x, y))))
+}
 
-  x <- plyr::ddply(x, c("Year", "Month"), average_monthly_values)
-  x <- plyr::ddply(x, c("Year", "Month"), calc_limits_by_period)
-  x <- dplyr::filter_(x, ~Values >= 5 & Weeks >= 3)
+assign_30day_periods <- function (x, dates) {
+  dates <- unique(dates)
+  y <- unique(dplyr::select_(x, ~Date))
+  y <- dplyr::arrange_(y, ~Date)
+  is.na(y$Period) <- NA
+
+  period <- 1
+  start_date <- y$Date[1]
+  y$Period[1] <- period
+
+  if(nrow(y) > 1) {
+    for(i in 2:nrow(y)) {
+      if(abs_days_diff(start_date, y$Date[i]) > 30 | y$Date[i] %in% dates) {
+        period <- period + 1
+        start_date <- y$Date[i]
+      }
+      y$Period[i] <- period
+    }
+  }
+  x <- dplyr::left_join(x, y, by = "Date")
+  stopifnot(noNA(x$Period))
+  x$Period <- factor(x$Period)
+  x
+}
 
-  if(!nrow(x))
-    return (x)
+average_30day_values_variable <- function (x) {
+  stopifnot(!is.unsorted(x$Date))
+  x$Samples <- nrow(x)
+  x$Span <- abs_days_diff(x$Date[1], x$Date[x$Samples])
+  txt <- paste0("x$Value <- ", x$Average[1], "(x$Value)")
+  eval(parse(text = txt))
+  x[1,,drop = FALSE]
+}
 
-  x$Date <- as.Date(paste(x$Year, x$Month, "01", sep = "-"))
+average_30day_values <- function (x) {
+  plyr::ddply(x, c("Variable"), average_30day_values_variable)
+}
 
-  stopifnot(!anyDuplicated(x$..ID))
+calc_limits_by_30day <- function (x, dates) {
+  ccodes <- get_conditional_codes(x$Condition[x$Term == "Long"])
+  x <- dplyr::filter_(x, ~(!is.na(Term) & Term == "Long") | Code %in% ccodes)
+  x <- dplyr::arrange_(x, ~Date)
+  x <- assign_30day_periods(x, dates)
+  x <- plyr::ddply(x, c("Period"), average_30day_values)
+  x <- fill_in_conditional_codes(x, ccodes)
+  x <- plyr::ddply(x, "Date", calc_limits_by_period)
 
-  x <- dplyr::select_(x, ~-..ID, ~-Code, ~-Average, ~-Year, ~-Month, ~-Values, ~-Weeks)
+  stopifnot(!anyDuplicated(x$..ID))
+  x <- dplyr::filter_(x, ~Samples >= 5 & Span >= 21 & !Conditional)
   x
 }
 
-calc_limits_by <- function (x, term, messages) {
+calc_limits_by <- function (x, term, dates) {
   x <- join_codes(x)
   x <- join_limits(x)
 
-  #  if(term == "long") {
-  #    x <- calc_limits_by_30day(x)
-  #  } else {
-  x <- calc_limits_by_date(x, messages = messages)
-  #  }
+  if(term == "long") {
+    x <- calc_limits_by_30day(x, dates)
+  } else {
+    x <- calc_limits_by_date(x)
+  }
   x <- dplyr::select_(x, ~Date, ~Variable, ~Value, ~UpperLimit, ~Units, ~Term)
   x
 }
@@ -129,18 +165,20 @@ calc_limits_by <- function (x, term, messages) {
 #'
 #' @inheritParams calc_wqis
 #' @param term A string indicating whether to calculate long-term or short-term limits.
+#' @param dates A date vector indicating the start of each 30 day period.
 #' @examples
 #' \dontrun{
 #' demo(fraser, ask = FALSE)
 #' }
 #' @export
-calc_limits <- function (x, by = NULL, term = "long",
+calc_limits <- function (x, by = NULL, term = "long", dates = NULL,
                          messages = getOption("wqbc.messages", default = TRUE),
                          parallel = getOption("wqbc.parallel", default = FALSE)) {
 
   assert_that(is.data.frame(x))
   assert_that(is.null(by) || (is.character(by) && noNA(by)))
   assert_that(is.string(term))
+  assert_that(is.null(dates) || (is.Date(dates) && noNA(dates)))
   assert_that(is.flag(messages) && noNA(messages))
   assert_that(is.flag(parallel) && noNA(parallel))
 
@@ -152,10 +190,10 @@ calc_limits <- function (x, by = NULL, term = "long",
   if(messages) message("Calculating water quality limits...")
 
   if(is.null(by)) {
-    x <- calc_limits_by(x, term = term, messages = messages)
+    x <- calc_limits_by(x, term = term, dates = dates)
   } else {
     x <- plyr::ddply(x, .variables = by, .fun = calc_limits_by, .parallel = parallel,
-                term = term, messages = messages)
+                     term = term, dates = dates)
   }
   if(messages) message("Calculated.")
   x
diff --git a/R/utils.R b/R/utils.R
index 2c67963..5fc7fda 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -89,3 +89,4 @@ proj_bc <- function (data, x, y, input_proj = NULL) {
 }
 
 is.error <- function (x) inherits (x, "try-error")
+is.Date <- function (x) inherits (x, "Date")
diff --git a/demo/dummy.R b/demo/dummy.R
index 824d6bb..9d98d2a 100644
--- a/demo/dummy.R
+++ b/demo/dummy.R
@@ -10,4 +10,4 @@ print(filter(dummy, !ID %in% dummy_standardized$ID))
 dummy_cleansed <- clean_wqdata(dummy_standardized, messages = TRUE)
 print(dummy_cleansed)
 
-dummy_limits <- calc_limits(dummy_cleansed, messages = TRUE)
+dummy_limits <- calc_limits(dummy_cleansed, term = "short", messages = TRUE)
diff --git a/demo/fraser.R b/demo/fraser.R
index e9c66e7..378412f 100644
--- a/demo/fraser.R
+++ b/demo/fraser.R
@@ -9,7 +9,8 @@ data(fraser)
 fraser$SiteID <-  factor(sub("BC08", "", as.character(fraser$SiteID)))
 plot_map(fraser, fill = "SiteID")
 
-fraser_limits <- calc_limits(fraser, by = c("SiteID", "Lat", "Long"),
+fraser_clean <- clean_wqdata(fraser, by = c("SiteID", "Lat", "Long"), messages = TRUE)
+fraser_limits <- calc_limits(fraser_clean, by = c("SiteID", "Lat", "Long"),
                              messages = TRUE)
 
 fraser_limits$Year <- year(fraser_limits$Date)
@@ -17,4 +18,4 @@ fraser_wqis <- calc_wqis(fraser_limits, by = c("SiteID", "Year", "Lat", "Long"))
 
 plot_wqis(fraser_wqis, x = "Year") + facet_wrap(~SiteID)
 
-plot_map_wqis(filter(fraser_wqis, Year %in% c(1990,2010)), keep = "Year") + facet_wrap(~Year, ncol = 1)
+plot_map_wqis(filter(fraser_wqis, Year %in% c(2000,2010)), keep = "Year") + facet_wrap(~Year, ncol = 1)
diff --git a/man/calc_limits.Rd b/man/calc_limits.Rd
index 0a9314a..9fbfdd9 100644
--- a/man/calc_limits.Rd
+++ b/man/calc_limits.Rd
@@ -4,7 +4,7 @@
 \alias{calc_limits}
 \title{Calculates Water Quality limits}
 \usage{
-calc_limits(x, by = NULL, term = "long",
+calc_limits(x, by = NULL, term = "long", dates = NULL,
   messages = getOption("wqbc.messages", default = TRUE),
   parallel = getOption("wqbc.parallel", default = FALSE))
 }
@@ -15,6 +15,8 @@ calc_limits(x, by = NULL, term = "long",
 
 \item{term}{A string indicating whether to calculate long-term or short-term limits.}
 
+\item{dates}{A date vector indicating the start of each 30 day period.}
+
 \item{messages}{A flag indicating whether to print messages.}
 
 \item{parallel}{A flag indicating whether to use the parallel backend provided by foreach.}